Don't second guess your background . Pretty much everything you learn will in some way be useful for you , and I have friends in data science from linguistics backgrounds , from pure engineering backgrounds , from physics backgrounds , from math backgrounds , it doesn't really matter . You can't learn everything in uni . You're going to have to learn something on the job .
You just need to appreciate the foundations you have and build on them .
Hello and welcome to Developers Journey , the podcast bringing you the making of stories of successful software developers to help you on your upcoming journey . I'm your host , tim Bologna . On this episode , I receive Jodie Brotel , dr Jodie Brotel actually , she is the developer advocate in data science at JetBrains .
Before that , she was a lead data scientist in Odian's Generation Advert Group , europe , after finishing her PhD in psychology and postdoc in statistics or biostatistics . Well , we'll have to see how that links to double .
Well , anyway , she has worked in various data science and machine learning roles across search improvements , recommendation systems , nlp and programmatic advertising . She's also very active in communities sharing knowledge in every possible form . Thus , you may have read her thoughts or seen her on stage or in a video somewhere actually everywhere .
Jodie , welcome Dev Journey .
Thank you so much . I'm absolutely delighted to be on the show .
I am as well , and we've been laughing for 20 minutes , which is great . Yes , and just for the fun . At the moment when we joined the Corp , we had a government alarm on all our telephones , a trial alarm which is blasted in our ears . That was a great way to start an interview .
It was literally me joining the call and saying it's bomb tag , like the warning day .
Exactly , and I wish I could have a warning like this to someone in the guest and say , hey , it's time to record , so really glad to have you on . But before we come to your story , I want to thank the terrific listeners who support the show . Every month you are keeping the Dev Journey lights up .
If you would like to join this fine crew and help me spend more time on finding phenomenal guests than editing audio tracks , please go to our website , devjourneyinfo and click on the support me on Patreon button . Even the smallest contributions are giant steps toward a sustainable Dev Journey journey . Thank you . And now back to today's guest , judy .
As you know , the show exists to help the listeners understand what your story looked like and imagine how to shape their own future . So let's go back to your beginnings . Where would you place the start if you're Dev Journey ?
Yeah . So I'm going to maybe do the cliched start and say it started when I was a kid , but probably not in the way that you think . So I think when a lot of people say , like , my Dev Journey started when I was a kid , it's because they got hold of a computer and they learned how to program . It's not exactly what I mean .
I actually didn't learn to program until I was in my mid-20s . What I mean is the core of what I see my work as like my whole life .
My whole passion in life is being a scientist , and when I was a kid I saw a Jurassic Park and I wanted to be a paleontologist , and this sort of obsession continued for years until I realized that when you're a paleontologist you have to spend a lot of hours in the sun digging up dinosaur bones , and that didn't sound like very appealing to me .
So then I thought , okay , maybe I can be an inventor or some kind of other scientist . And I had , you know , all those kids that kids have , like the microscope and the geology set and the chemistry set , like I loved all of it .
And then I went to high school and I realized that well , it wasn't , when I realized that science was different to what I thought it was .
It was just that it was not taught that well at my school I went to like a very small country town school in country town , australia , and you know we just didn't have the resources to really teach science in a way that was particularly engaging . It didn't help that most of the science classes focused on physics and physics is not . It doesn't interest me .
I'm sorry physicists , it's just it's not interesting for me . But I was kind of drawn to the humanities as a teenager . I used to play French horn , I used to like be in the school band , I did art , I did English history .
This was sort of what I studied towards the end of my high school and this sort of meant that when I got to the end of high school I didn't know what I wanted to do at uni , because I knew I wanted to go to uni .
I've always enjoyed school and sort of the academic side of things , but like I wasn't stupid , I knew I wasn't going to get a job if I like just studied English literature . So I was like , okay , I need to think of it practically .
So in Australia you have this ability to do what's called dual degrees , so you can study two completely unrelated degrees at the same time and you just complete them in four years instead of a three . So I enrolled in an arts degree , which is like the liberal arts degree is what they'd call it in the States , and I studied history and German .
Actually , I studied German at uni . It's the thing . I live in Berlin now and I forgot all the German I learned at uni . You'll see why in a second .
I won't throw a stone at you at all .
Thank you , thanks for being kind . Yes , and even after five and a half years in Germany my in German still not that good , but anyway and I enrolled in psychology , and how I got into psychology is kind of a funny story .
I was doing my final year art project and I did this very like pretentious art kind of critique kind of project and I kind of pulled in this stuff from Freudian and Jungian . Psychology was very pretentious and I was like this psychologist does , kind of cool , maybe I'll go study that .
Haha , psychology is a science and that is what I fell in love with and I like I fell in love with statistics , with research methodology , with measurement , and I fell in love with it to such a big degree that the German wasn't going so well , like I was getting worse and worse marks every semester .
So I was like I'm going to drop this arts degree and I actually changed to a dual psychology biology degree and so like I just did double sciences had a time in my life . I loved it and this was a story that I really love to tell everyone .
Towards the end of my biology degree I was studying evolutionary biology and I had the chance to do a research project and so basically , the research project was looking at this particular reproductive behavior and it's really easy to observe in crickets or get into the boring technical details , but essentially what it boiled down to was me sitting in a stinky lab for
three months watching pairs of crickets mating with this red light , and it was just like that was the point where I decided to do the PhD in psychology . Let's put it that way , not biology and not biology .
Yeah , Before you move on how did you decide to go into biology ? And I mean obviously not physics you told us about it before , but any other kind of scientific branch could have done it as well . Why biology , yeah ?
It was because we had to do some biology units as part of our first year's psych degree because like neuroscience and things like that . But they wanted you at my university to at least have a basic grounding in human physiology . So that was why and I really liked neuroscience as well . So , yeah , it was a pretty easy decision .
And once I started the biology degree I realized like I love evolutionary theory . I love it so much , it's so elegant and yeah , genetics as well and that was actually the genetics component was super helpful , I think , for some of the stuff I did in psychology later . But yeah , we'll probably talk about it a bit later .
I think as much fun as the biology degree was , I still kind of regret that I didn't pick something more practical like computer sciences or statistics with the way things turned out . But I think we'll come back to that .
Sure , let's go back to crickets . What happened after that ?
No , we finished the crickets , we were post-crickets . We're post three months in the stinky lab . So basically after that I enrolled in my PhD . But at that time again , I'm quite a practical person . So I was thinking I'm not entirely sure about academia . I really love doing the work but I know it's a hard career . So I really liked clinical psychology .
So I enrolled in this , like it's basically a PhD program where you have your masters in clinical psych squashed together with your PhD and you do them both together again kind of like the double degree . So I trained as a psychologist , like I was going and seeing patients for a year and a half part time . Like I was fully licensed as a psychologist .
I just never practiced because I was still finishing my PhD and this was probably my first big career fork . I was getting towards the end of my PhD and I was thinking , okay , I should probably start looking for a job as a psych and start thinking about what's the next step . I was like I don't want to do it . I really liked being with the patients .
I really liked helping people . It was amazing work . I feel so privileged that I got to do that work because to have the trust of people who are brave enough to go through therapy . To be able to help them is one of the most amazing things I've done in my life . But I knew I couldn't do it for my whole life .
It was something I took home with me a lot . It really affected me when people had really heavy things . It was too much for me . One of my supervisors was not very happy about this , but I just decided I wouldn't practice . I was like , okay , maybe I'll give this academia thing a go after all and I went into a postdoc .
I was very lucky to get the postdoc . I got it through a friend who knew the supervisor was looking for someone sort of switch courses . I went into biostatistics and public health .
Basically what I was studying was care patterns for people with acute cardiac events like heart attacks , and also palliative care so people at the end of life and seeing whether there were things we could do to improve hospital care triaging things like that Amazing time , my God . I learned so much .
It was probably one of my favorite times of my career in terms of the work . Like the scientific work , I felt like the work was having a really direct impact . But I couldn't hack it in academia either . It's just the published cycle is so severe , it's so hard . And again , I'm very practical .
I was looking ahead and I'm like if I can't make this work , I'm screwed . You can't leave academia after a certain amount of time . There's no way you can get a job . So at the end of my postdoc it wasn't that hard a decision I really was like I can't do this , and I was so lucky that at that time , data science was becoming a thing .
This was back in 2014 , 2015 . And so I didn't quite get what the job was , but I did have science in the title and I knew that I could basically make good money . I knew this was a thing . This was around the time when it was being called like the sexiest job of the 21st century , whatever is like proper hype time .
I didn't really know what I was doing . I applied to a whole bunch of jobs that I was severely underqualified for and I was very lucky that I ended up getting a job in more of a kind of like analytics role that really played to my strengths in like statistics . I knew some basic R at that point .
I had kind of played around with Python during my PhD when I was procrastinating for my thesis , but I'd never touched it again and , yeah , that was sort of where the actual data science career kicked off . But you can see it was pretty convoluted part of it . I left a couple of careers behind on the way , Like my 30s .
I look back at my 20s , I look back and I'm like Jesus Christ . Maybe I could have done this in a more efficient way , but it wouldn't be fun . It wouldn't be fun and I wouldn't have the amazing cricket sex stories .
So you know , there you go Hooking you back to what you said at the beginning . You said you placed the very start at realizing you want to be a scientist . Does this data science really match the idea you had before ?
It actually does , and this is something I guess I am pretty clear about when I talk to people about data science , because I think even now it's a field with a lot of misconceptions and as the field has matured , I think it's matured into a couple of different things .
So back in my day , data science used to be the refuge for failed academics , like this was . 80% of us were people who were like screw this , I want to go and you know , have some work-life balance and , you know , make a bit more of a stable career choice . It's changed a lot .
Actually it's changed a lot over the time I've been in the field and one of the big changes has been a lot of people coming in with developer backgrounds , so people coming in with more computer science or engineering backgrounds , and they lend their own particular perspective and it's been , I think , a natural evolution as the requirements of deploying machine learning
projects has become much more complicated , like large language models are one of the most extreme examples . But you know ML Ops is now its own thing and it kind of rightfully needs to be ML engineering , especially like specialized branches where people try to take big , complex models and make them leaner and more computer-efficient . This is another specialization .
So you've got this kind of new area which is more engineering focused .
But you will always have , in my opinion at least , this core group who are more on the research and scientific side and I don't think you can really do kind of proper prototyping , exploration , research work in data science without that scientific mindset that you need to think critically about . okay , is this data measuring what I think it's measuring ?
Is there bias ? Is there , you know , all these kind of basic scientific considerations ? Have I really looked at this at enough angles to feel comfortable that I've gotten the true story that this data wants to tell me and that's really all it is ? It's not all it is . It's hard to learn these skills but , like at the core of it , that's what it is .
It's a scientific relationship with the data .
It is indeed . It is indeed At least when you are lucky enough to have this data engineering somebody doing the data engineering part with you and you can focus on that part . Early stage startup , for instance , when you have to do all and everything at the same time , you have to put some consideration aside .
But at some point you really have to embrace those and take them into consideration , and that's where you probably shine .
Yes , yes , and it's been an interesting part of my journey as well . So I guess , maybe just going a little bit back into the timeline of the story , when I first started working on the technical side of things , this was really hard for me . So , if you think about it , what I had spent 11 years at uni doing was training towards the same set of skills .
And even though it's hard in academia because people will really evaluate you , they'll really question you , sometimes they will insult you about whether your skills are good enough yeah , it's academia . I once had a paper of you that questioned whether I , like , should be in science at all , and I went and cried in the bathroom .
A lot of crying in the bathroom in my postdoc . Wow , yes , academia , yeah , shout out to my peeps who are still there in the audience .
At least you can laugh about it now .
Yeah , yeah , it's been like 10 years since I've finished my .
PhD , so they're still behind me now .
But it was kind of funny because then I had this skill set that I'd been honing for years and I was super comfortable with that skill set and then I had to turn around and learn a new skill set which was super foreign .
I will confess I was so lucky that my now husband he and I had just started dating and he is a developer and had been developed for a long time and he's very non-judgmental and he's very good at teaching . But I remember the first time I tried to read in a file in R , he told me two hours because I had the slashes the wrong way .
I was like working from a book that was written for Linux systems and I was working on a window system , like again started crying . This is what happens . There's a lot of points of crying in my career . Like I was super scared about using the command line because I was convinced I was going to break the computer .
Like it looks like something from a 90s Hackers movie , like if you're not familiar with it , and this was the thing at the beginning of my career that I think actually really hamstrung me a lot because I was so insecure about my engineering skills as soon as I got the slightest bit of pushback , like I got questioned by I don't know .
You know , some developers can be a bit like that , like , oh , you don't know this . I'd be like , yeah , I don't know this , I'm a huge idiot , like , and I really let it get to me . I kind of wish that I'd been a bit more confident back then . But you know , how can you wish for confidence , you know ?
Yeah , once I got my feet under me with the engineering staff and I realized actually , like some of it is generally very difficult , some of it seems difficult but it's not that hard I decided to see how far I wanted to go down the path of learning engineering skills and I got very I mean , yeah , I would say I got lucky in my third job in industry .
So I started working at what was the kind of medium size startup ended up getting acquired just before I started and I worked on a team with two guys who are like true machine learning engineers , like they can do everything from you know your research , prototyping stuff to like fully maintaining things in production , and they both really smart , really nice , and
they took a lot of time to teach me things and I kind of came to the conclusion I don't want to do the engineering side . I saw enough of it and I'm like I don't like it .
But it was sort of this journey of me exploring incrementally like okay , I know the scientific side , how far down the engineering path to I want to go and in the end I came to the conclusion it's not for me and I'm totally fine with that decision .
And it also means that I have like a , I think , a full understanding and even more respect for the job that engineers need to do .
It made it easier for me to work with the engineering staff and I'm like I'm not going to be doing it with engineers because I could explain the requirements a little bit better or I knew when I just didn't understand and I just needed to tell them what I needed to be done and just leave it all to them . So I think that is a super important thing .
With any career , you'll never work alone and you should never just dismiss one of your colleagues as , like whatever , like you need to respect that there's different specializations . They take time to learn . I think something I've seen other like especially ex-academic data scientists doing is having a bit of arrogance and being like I'm smarter than everyone .
I have PhD , so I'll just do this engineering thing because it's not that hard and I've seen stuff they built and it ain't good . Yes , I can .
Now , both sides of the equation are really hard and you really need to start dipping your toes , whether you're on one side or the other , onto the other side and really grasp an understanding of what's happening , and it's really eye-opening and empathy empathy building and really helps you work with people , be a bit of human . It's all encompassing .
Yeah , and look like maybe a lesson I also learned from academia is I was so wrapped up in my work as an academic . It was such an important part of my identity that when I left I was actually very lucky with my first job , got lucky with a lot of jobs , but even just really good at spotting crapping interviews . They were so chill .
And so about work-life balance at this place . Like we would stop at 3pm on Friday for beers . Like it was kind of just like you would get rounded up by your manager and just like come on , we're going downstairs for beers , yeah , australia you know , can recommend .
I imagine that would be Germany , but okay .
Yeah , and Germany's also , but that's at 5pm . Come on , you've got to finish your hours for the week and then .
That's true , yeah .
But yeah , this sort of complete change of pace meant that I don't take work so personally anymore , like I'm way more chill about it and that's great . I don't move to Germany , the land of work-life balance , and it's amazing , it is , it's so good .
Did you notice an effect on how you approach things the way that you I mean the fact that you are in less pressure , you have a better life balance . Did you realize an effect on how you go at your work , the result , the outcomes , maybe ?
This is a really interesting question . So I would say , I would say I'd like to think I always sort of had like patience and empathy , because I kind of had to learn that as a psychologist . But I think it just sort of let me let things go a bit easier .
So it meant that I don't know if someone doesn't get something back to me like in time , and it's not that important , I just let it go . I don't care because I'm like whatever you know , it's not the end of the world , it's just my job .
It is very important to me and it's very important to do my job properly and be a good employee , but I guess I don't take things personally . I don't . Maybe it's also I don't care when people question my career choices and they don't and they question my skills because I chose to do the things that make me happy .
Yeah , I'm aware that definitely I have weaknesses in certain areas , but I'm fine with the choices I've taken at this stage , and maybe that's part of stepping back , because in academia I would take it all so personally and I'd feel devastated if people questioned , you know , my competence in certain fields .
It's been , I think , one of the biggest gifts of walking away from academia for me this ability to have a much healthier relationship with my job .
Do you think it's really ? This is a loaded question , sorry , do you ? Think it's really the stepping away from academia , or having 10 or 15 years of experience later , or looking at it 15 years later .
I think it's both Like . I think if I personally had stayed in academia and look this is not something I want to say across the board , because I have friends who are still in academia and they've found a way to make it a job I think for me personally it just pushed too many buttons .
It pushed buttons that I guess I wasn't even aware I had until I left . It was funny when I first left academia I was really still in this mindset .
In academia , at least in the universities I was at , there was this real pressure that things had to be prestigious , you had to start publishing prestigious journals and you had to work at the right institutions , you had to know the right people . That just somehow really pushed my buttons .
Maybe again , maybe nowadays it wouldn't because I'm older , but when I first left I was kind of like okay , my goal is to work at a fang , because that's transferring the mindset immediately . Then I actually started to think about what I want to do day to day at work or make me happy , and I'm like well , maybe it wouldn't be the right fit .
Like , if it is the right fit later on and I happen to be lucky enough to get a job there , maybe that could be part of my career , but it's not for the same reason anymore . But definitely , getting older is amazing and you just care so much less about so many things . So , yeah , I think you're right .
It's a combo of both , but with my particular personality , I'm very intense . Academia was not an amazing fit for that .
I can see why you were talking about this third job and going deep and realizing not your knowledge , not your cup of tea . But you're glad you went at it , learned it and now are able to observe the other side Later on . I'm not sure which job it is number two , three , four , five .
You made a choice , an interesting choice , of going into developer advocacy for legacy and still , but this is a fork . Can you tell us more about that ?
I was wondering when we were going to come to this , because this is the last career change , the final one Well , maybe the final one so far .
So , yeah , developer advocacy this was not on my radar , this was not something I was working towards and I have a good friend she also works at JetBrains as a dev advocate , and we were just chatting before Christmas and she mentioned this job , my current job , and she's like hey , you should apply for it .
I'm like , well , I'm not really looking and I don't think this is the right fit , because I felt like I was with sales and I was like I don't want to do sales and she's like , no , no , no , no , no , it's not sales . She explained JetBrains has a particular outlook on developer advocacy .
So basically , the idea is you are trying to act as liaison between your community and the product and you can kind of do this however you like , but the main thing is , first and foremost , you are the career that you came in with .
You're not an influencer , you're not a developer advocate , you are a data scientist , you are a job developer , you are this , that and the other . So that obviously was important to me because we've talked about this . My obsession in life is science , so I didn't want to leave that behind .
But the other thing is you have the ability to do the job however you like , and that is super important for me . I need a very long leash and it's also important for me to be a genuine person . So part of the job is I get to help other people . It's not that I get to help them become better pie charm users , but sometimes that's part of the job .
It's that I make it easier for them to get into data scientist or get over barriers they're having in data science . It's personally really important for me because of those feelings I told you I had when I started . There were a couple of people who were super cool at supporting me when I got in . One of them was a mentor at my first job in Australia .
I kind of want to be that person for other people , maybe not in a one-on-one fashion , but just being able to be a voice to say , hey , my background is super non-engineering , but here I am and I'm happy and I've made a career doing this .
And then the other thing is I love to learn , obviously , to say to school for a long , long time and you get a lot more opportunity to get your hands in the cool new stuff that's coming out . So , yeah , that's why I made the switch . It's not necessarily a natural continuation , I would say , of my data science career , but maybe it's kind of .
It feels almost like being back in academia , but without the toxicity . Being able to work on projects that I like , being able to follow my intuition about what will be fruitful area it's . Yeah , it's a really fun job and you're never bored and it's always something new to do . Like I'm flying to London next week for a conference .
I think by the time this episode comes out , I will be in San Francisco for another one and then I'll be in Lithuania two weeks after that . So that definitely keeps me busy . But , like , on top of that , it's just what I get to do at those conferences . I get to talk to people , I get to meet cool people , I get to , like help out with community events .
It's a nice job .
I'm trying to piece that . I know developer advocacy from the developer standpoint , but it's the first time I hear it from a data science or non-developer role , although data science still contains a lot of development , but not , not , not not not different .
Yeah , it's a bit different .
The way I picture it is you have a lot of community work , you have a lot of working with people , but this scratching the science itch that you have is it only your own projects ? And then you have on top this whole .
I'm going to picture it as an overhead of stuff you do as a developer advocate and you're scratching this itch on your on your , on your personal project . You're nodding right now . Oh , oh , do you find this , this a science-y part in the rest of the job as well ?
It's . It's an interesting question . So you're right that , like like all the developer advocates , it's really just your own projects . So scratching the itch of direct data science work comes through projects that I work on , but I would say for me the itch gets scratched in a couple of other ways .
So just even learning about new technologies can be like intellectual work , like it is .
It is .
Yeah , and so just reading about new developments that really scratches the itch for me . And it's not just , I would say , like the pure , like , say , model architectures or , you know , learning about how to run X thing on XGPU .
It's even things like and this is why large language models for me now are super exciting , apart from the fact that my background is natural language processing . It's the like the debate got into an area that is personally extremely interesting , given my psychology background .
There is so much work now about the measurement of things like bias , the measurement of toxicity , the measurement of truthfulness . This is oh , this is going back to stuff I haven't touched for over 10 years . And it's also the other kind of third arm I would say is science communication .
It's always something I enjoyed and it's something that I actually see as integral to science . Like , you can't write a paper if you can't communicate right . So being able to explain difficult technical concepts in a digestible way , that scratches an itch for me as well , because that , for me , is science communication .
It's intellectual work , it's and it's personally very satisfying because you feel like you're going to empower someone with that .
Yeah , makes a lot of sense . Did you see yourself using more and more this psychology I'm going to put it second career that you had as it enters the large language modeling and NLP , et cetera , world .
Actually this brings us back to the conversation that I ceded earlier about regretting my second degree , kind of , but never the psychology degree . So the reason I regretted my biology degree not really . I had an absolute blast doing it . I learned lots of cool stuff .
But it would have been really practical to have something like computer sciences or statistics in my undergrad when I was young , when I had the energy to learn all this , instead of having to learn it bit by bit , which is how I've had to do it over my career . But the psychology qualification I regretted it .
Initially I was really beating myself up when I left even actually my postdoc , I was kind of beating myself up about it , but definitely when I left I was like shit , why did I not study physics ? Why did I not study something that I see all the other data scientists study ?
What I've actually come to realize is the core of what I learned in my degree is the measurement of behavior , and that is such a broadly applicable skill . So all of the work that I have done in data science in my career has been in some way related to this . So I worked with language , languages of behavior .
I worked with how customers interact with a website . That's behavior I worked with how these programmatic systems interact with each other . It's not human behavior , but it's still behavior . And then , of course , now we're getting into much more core psychology topics with large language models .
But the whole way it's actually been really valuable , and it took me a long time to appreciate it , but it's kind of amazing what kind of skills I learned and I just took for granted . It is fun .
Coming back to topics , though , that are core to what I studied , I can appreciate that I did a very traditional general engineering degree in France and when I entered the industry I said , oh crap , I'm getting my ass served by apprentices who did 10 months of programming and they can program better than me .
And it took me 15 years to really appreciate the spectrum of stuff I learned and how applicable it is in every sense of the way . But it took 15 years .
Yeah , and maybe that would be maybe some advice I'd have for any listeners that are starting their career . Don't second guess your background .
Pretty much everything you learn will in some way be useful for you , and I have friends in data science , from linguistics backgrounds , from pure engineering backgrounds , from physics backgrounds , from math backgrounds , it doesn't really matter . You can't learn everything in uni . You're going to have to learn something on the job .
You just need to appreciate the foundations you have and build on them .
Everything you learn will be useful , even the crickets .
Well , it is . Yeah , maybe it's not directly , it's like about a life At least one You're going to come back .
I'm sure they're going to come back .
I think like let's wait 10 years and somehow I'm going to deep . Knowledge of sexual selections in other pods will become extremely useful , let's hope not Never seen ever Max playing . Come waiting for your call .
Do you have an idea of where you want to take your career from now ? Are there scratches ? Each is you want to scratch and that you haven't so far .
Look , I think probably the only question mark for me is going fully back into the areas that I fell in love with in undergrad . One of the things that broke my heart a little bit when I left academia was leaving behind health sciences as a topic area . I don't think anything has ever kind of made me as happy as studying health sciences .
I loved the domain in my postdoc . I loved the domain in my undergrad . I loved the crickets . It would be super cool if in some way I could find a way to work that back into my career . That said , right now I'm pretty comfortable . Who knows if there's going to be a return to pure data science roles .
The question mark for me about going back to a pure data science role and look , this would be in many years I'm very comfortable . It's sort of I tried doing the team lead thing . We talked about how this is your day-to-day job before we started this recording . It wasn't my favorite thing .
I would say I'm not exceptionally great at it Because , again , it's the same thing I have when I was a psychologist . I take it home with me . I don't know , maybe technical team leadership . It does sound appealing , but definitely not having , I think , the care and nurturing of your employees . It's very heavy .
It takes a certain type to be able to be able to juggle the demands of the business with the well-being of your employees . It's a hard job .
It is indeed . It is indeed . Not everybody is , I don't want to say cut for it , but ready for it . It's really something you have to learn . You're not ready from the get-go to do this . You really have to learn it .
I think something people don't appreciate is you have two masters . Firstly , you've got upstream and downstream . It's also that people are complicated . You're not just going to be dealing with their work concerns , but you still need to set boundaries . I'm always very nice to my bosses . Especially after I was a boss , I was like gosh , this is so hard .
There's a fantastic article from Charity Majors called the engineering manager individual contributors of Pendulum . She really advocates for going toward management and understanding what it means to be a manager , then coming back to individual contribution enriched with this knowledge and really with the empathy of saying I know what my bosses is feeling .
Now I can work with that and become a better individual contributor . And working with my boss , then at some point going back maybe and learning some more and then going back and forth and not sticking to one side or the other forever . Which ?
is interesting . Yeah , Although easier said than done , I guess , because I have heard maybe you can confirm that it tends to be a reluctance to let people who have done management for too long I'm using air quotes like kind of an idea that they can't do individual contribution anymore yeah , which I don't think it's yeah .
You have to work on your profile and making the air quotes as well . On your profile while being a manager if you want to still be seen as an individual contributor .
In the company I work for right now , we really explicitly created the profiles to say , when you're a first time manager , you're both and we really explain both and it's in your job description that you are both , so that you don't feel trapped into sticking to this role .
And only when you start becoming a manager of a manager , it becomes a career choice to really stick to management and then probably you cannot really go back . But by that time you have acquired skills that are really unique and probably left some part of IC behind . But still , you dropped a fantastic advice already of not second guessing your careers .
But there's another one I would like to ask you Go ahead , because you have a very unique decision point in your story of quitting academia and really changing careers .
What would be the advice we give to somebody considering this , having really had a career on their hands and really being deeply passionate about it and facing the question should I quit and do something else , or should I change and embrace something else ?
Yeah , this is such a nice question and it's actually very good timing because I'm writing a talk that I'm going to give in next month , which is not quite on this topic but it touches on it . So , I guess being aware of what you're getting into .
So when you're an academic , the idea is that you go so deep into a topic that you're able to publish an original piece of research finding something new , and it has , like it's so rock solid that you are fairly sure you're contributing a piece of truth to the scientific literature . That's not what you're going to be doing in business .
Basically , what you need to think about is you are hired into a company that needs to cover costs , and if it's a for-profit company , they also need to make some money . So you need to be providing some value .
And something I had to learn very , very quickly is you're not going to have the same kind of time frames , which means you can't be as sure about what you're presenting . You kind of have to be sure enough or try to verify things in a different way , like with machine learning , make sure that it works on a validation set and a test set .
Like maybe that's probably as solid as you're going to be able to be about what you're doing .
The other is you know , if you start a project and you're given X amount of time to research and it doesn't seem to be panning out good chances , it's just going to get scrapped because business doesn't have time to be messing around on something that , like it , depends on the project , depends how important it is to get it working .
But if it's just an idea you had and it's not looking promising after the amount of time they've given you , it's probably going to get chalked . So it is a much more let's say it can feel more mercenary , but it's not a bad thing either .
Like , to be honest , the payoff you get is that you'll often be building products that you can see people using in the real world . Like I built part of a recommender system . I still see my recommendations coming through like six years later . That's really cool .
I helped contribute to the efficiency of a search engine and , like obviously I can't see the direct results , but I know that work I did improved , that it's a trade-off and you need to be prepared for the fact that the rigor that maybe you enjoyed about being a scientist will need to be compromised .
But the payoff is you get a lot more stability and well , maybe if you're a better academic than I was , you can have that stability and you'll get like a payoff with you will see things that you researched , that you found , that you built actually being used , which can't always say for academia .
Often , cannot Indeed and it's very rewarding . So you have to water your wine a little bit .
Yes .
Really let the emotions go , understand business and get the reward of doing a little bit less science , maybe getting the rewards of seeing your products actually built and used and get the reap , the benefits of that .
Yeah , yeah , you have to accept that you'll still be doing science , it's just to a different level of rigor with a different goal .
Amen to that . Judy thank you so much . Where would be the best place to continue this discussion with you ?
I want to say thank you as well . I had a wonderful time . So few places to contact me . I have a Twitter account . I'm never going to call it . X . I'm sorry , who knows , maybe at the time this episode is released you will have changed the name back .
Indeed .
I have a mastodon account . I have also a website , which I've been . Actually , it was what I started when I left academia , so that's been running since about 2015 , on and off , not that . And then , of course , you can always reach out to me on LinkedIn , so you just shoot me a DM if you want to get in touch and have any questions .
I'll add all those links to the show notes If you don't have to search . Just scroll down and it will be all there . Anything else to plug in before we call it a day ?
No , I think that's everything .
That was fantastic . Thank you so much .
Such an interesting roller coaster , thank you so much and thanks for letting me tell some of my favorite stories , even though they're a little salubrious .
I'm glad we talked about the creates . Yes , judy , thank you so much . Thanks , and this has been another episode of Dev's Journey and we see each other next week . Bye , thanks a lot for tuning in . I hope you have enjoyed this week's episode . If you like the show , please share , rate and review . It helps more listeners discover those stories .
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