Careers In Science public
[search 0]
More
Download the App!
show episodes
 
Artwork

1
Build a Career in Data Science

Jacqueline Nolis and Emily Robinson

Unsubscribe
Unsubscribe
Monthly
 
Build a Career in Data Science teaches you what data science courses leave out: from how to land your first job to the lifecycle of a data science project and even how to become a manager. This is a true how-to on obtaining and then navigating a data science career--filled with real stories from data scientists. This podcast is an extension of the similarly named book: Build a Career in Data Science.
  continue reading
 
Loading …
show series
 
This very surprise bonus episode was made after Emily and Jacqueline found themselves simultaneously unemployed. Here Emily will chat about being part of a 15% company-wide labor reduction while Jacqueline walks through the steps she's been doing as she interviews with new companies. Join them for some vulnerable conversation that are relevant to t…
  continue reading
 
In this special live episode recorded at PyLadies London, Emily and Jacqueline discuss those little subfields of data science like experimentation and fraud. They ponder the benefits of becoming more specialized in your career and how different fields have different cultures. The episode ends with a Q&A using live audience questions!…
  continue reading
 
In this special live episode recorded at the Data Science DC, Emily and Jacqueline talk about data scientists' relationships with their managers. They discuss how you should communicate with your manager, how much you should be doing what your manager asks vs what you think is best for the company, and other topics. Several times in the episode Jac…
  continue reading
 
After you are a senior data scientist for a few years, what is next? In this episode Jacqueline and Emily talk about three possible career moves for seasoned data scientists: becoming a manager, a technical lead, or an independent consultant. They discuss the pros and cons of the different types of jobs and strategies for getting into those roles.…
  continue reading
 
"You can't fire me I quit!" --a great example of not leaving a job gracefully (but hey it happens!). In this week's episode Emily and Jacqueline discuss how to decide when the right moment is for you to leave a job, and what steps you should take. They also talk about the realities of the situation, like managers who don't seem to listen when you d…
  continue reading
 
Social media, conferences, blogs, and meetups--there are many places where data scientists congregate outside of work. But how does a data scientist become a part of these communities and contribute? In this episode Jacqueline and Emily discuss speaking at conferences, awkwardly attending your first meetup, and many other moments that can happen wh…
  continue reading
 
You're not a failure! The field of data science is overflowing with projects that just didn't work out. This episode we talk about these projects and why they fail. We also discuss how to handle them emotionally even though it might feel like you're solely responsible. In the game, Emily makes Jacqueline try and discern true stories of data science…
  continue reading
 
Putting data science into production can mean a ton of things: from customer-facing models run millions of times a day to continuously live dashboards for stakeholders. But writing code for production and getting it to work can be intimidating for many data scientists, and lots of us have never tried. In this episode we talk about production, why i…
  continue reading
 
An analysis is the work of taking data and turning it into a PowerPoint presentation (more or less), and in this episode we talk all about it. What makes an analysis sharp, how to sell data stories to stakeholders, and the useful tool of an "analysis plan" are all discussed. The episode ends with Emily giving Jacqueline an analysis game that tangen…
  continue reading
 
Welcome to your new data science role! You just started a new data science job, maybe your first one, and wow there is a lot to do! In this episode, we cover what to expect in the first few months of the job and what to do if it’s not what you hoped. We also discuss how to handle the inevitable heartbreak as you find technical skeletons in the clos…
  continue reading
 
Technically still just in time for the last of the holidays - a special bonus episode! Here we cover three small mini-topics. First, whether you should get a PhD to become a data scientist (spoiler alert: almost certainly not), delving deep into the culture of academia and our own PhD experiences. Then we share how we decide if we should learn a ne…
  continue reading
 
Stop! Don’t just accept that coveted data science job offer right off the bat. Instead, listen to this episode where we discuss negotiating: what’s on the table, what salaries to expect at different levels of data scientist, what the heck RSUs and stock options are, and much more. By reflecting on what’s important to you and how to ask for it, you’…
  continue reading
 
The interview: possibly the most nerve-wracking part of a data science job search. In this episode, we’ll help you prepare by covering the full interview process, including the different types of interviews, what questions you might be asked, and what the interviewers are looking for. And since interviewing is a two-way street, we also do a mock in…
  continue reading
 
“You only get one chance at a first impression.” When applying for data science jobs, that’s usually your resume (and sometimes a cover letter). So how can you give your data science resume the polish it deserves? In this episode, we discuss what hiring managers and recruiters are looking for in a resume, how and why to customize it for different j…
  continue reading
 
Perhaps the most common piece of advice for aspiring data scientists is to make a project portfolio. Despite this, so few data scientists do so! In this episode, we discuss what exactly a portfolio is, the benefits, and the common reasons people don’t do it and how to overcome them. Spoiler: it's just as much psychological as it is about time and s…
  continue reading
 
It seems there are so many “required” skills for a data science job—how can someone possibly learn them? In this episode, we discuss four possible ways to do so: a formal degree program, a boot camp, learning on the job, and teaching yourself. We also share our own very different backgrounds: Jacqueline's math master's and engineering PhD versus Em…
  continue reading
 
While the popular image of a data scientist is one solving cutting-edge problems at a large tech company, data scientists work in every type of organization. In this episode, we talk through five company archetypes, from small start-ups to government contractors to traditional retail companies. We weigh the pros and cons of working at each and deba…
  continue reading
 
What actually *is* data science, and what does a data scientist do? What kind of backgrounds do data scientists come from and what skills do you need to be one? In this episode we start with the basics—declaring once and for all what is data science anyway and exploring how the hype of the field matches reality. We explore the three main areas of d…
  continue reading
 
Return From Hiatus! Guest starring Buddy Black Our new Guitarist: CHAZZ, The Worst Improve Participant, GTA V, Duck Tales, Gargoyles, How to skip the worst Next Gen Episodes & not become a Fairy by watching Jem & The Holograms. Segments include Failures In Eric's Dating & Buddy Black introduces new shapes and talks about his marriage...and argues w…
  continue reading
 
Loading …

Quick Reference Guide