Jacqueline Nolis and Emily Robinson
Build a Career in Data ScienceEpisodes
Episodes of Build a Career in Data Science
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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 doi
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
In the final episode of Season 1, Emily and Jacqueline take a moment to reflect on all they've learned in writing a book and making a podcast about data science careers.
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
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. T
"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 ta
In this special live episode recorded at the ODSC East conference, Emily and Jacqueline discuss what to think about it you can't seem to find that data science job you want. They talk about the different reasons why job hunts don't work, what y
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
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 y
Stakeholders! The people who data scientists help by creating analyses and models. Stakeholders have so many needs, and keeping them satisfied is one of the most important parts of being a successful data scientist. In this episode Jacqueline a
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
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 "an
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
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 int
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
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, a
“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 wh
Before you can get a data science job, you need to find one! In this episode, we discuss how to decode job descriptions, use your network, and find jobs that don’t need 3+ years of experience. We share how we’ve found our previous jobs and we d
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 peopl
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.
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 gove
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 sc
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