Chapter 7: the Job Interview

Build a Career in Data Science

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תוכן מסופק על ידי Jacqueline Nolis and Emily Robinson, Jacqueline Nolis, and Emily Robinson. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Jacqueline Nolis and Emily Robinson, Jacqueline Nolis, and Emily Robinson או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

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A secret field that summons lightning. A massive spiral that disappears into a salt lake. A celestial observatory carved into a volcano. Meet the wild—and sometimes explosive—world of land art, where artists craft masterpieces with dynamite and bulldozers. In our Season 2 premiere, guest Dylan Thuras, cofounder of Atlas Obscura, takes us off road and into the minds of the artists who literally reshaped parts of the Southwest. These works aren’t meant to be easy to reach—or to explain—but they just might change how you see the world. Land art you’ll visit in this episode: - Double Negative and City by Michael Heizer (Garden Valley, Nevada) - Spiral Jetty by Robert Smithson (Great Salt Lake, Utah) - Sun Tunnels by Nancy Holt (Great Basin Desert, Utah) - Lightning Field by Walter De Maria (Catron County, New Mexico) - Roden Crater by James Turrell (Painted Desert, Arizona) Via Podcast is a production of AAA Mountain West Group.…

לפני 4 שנים 1:03:31

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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 interview where Emily as the interviewee tries to see if there are red flags in a few jobs.

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#Careers #Business #Jacqueline Nolis and Emily Robinson #Emily Robinson #Jacqueline Nolis

Build a Career in Data Science

Chapter 7: the Job Interview

Build a Career in Data Science

40 subscribers

published לפני 4 שנים

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MP3•בית הפרקים

22 פרקים

#Careers #Business #Jacqueline Nolis and Emily Robinson #Emily Robinson #Jacqueline Nolis

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Build a Career in Data Science

1
Oops! We're Both Unemployed!! 1:00:49

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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 doing as she interviews with new companies. Join them for some vulnerable conversation that are relevant to this current wave of layoffs.…

Build a Career in Data Science

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Interlude: Data Science Subfields 54:49

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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!…

Build a Career in Data Science

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Epilogue: So What Have We Learned? 38:05

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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.

Build a Career in Data Science

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Interlude: Managing Your Manager 52:18

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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 Jacqueline and Emily disagree, adding drama and intrigue.…

Build a Career in Data Science

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Chapter 16: Moving up the ladder 1:03:52

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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.…

Build a Career in Data Science

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Chapter 15: Leaving Your Job Gracefully 56:05

לפני 4 years56:05

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"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 discuss why you are unhappy, walking out of job, and getting a last minute counter offer.…

Build a Career in Data Science

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Interlude: Help! My Job Search Isn't Working 37:11

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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 you can do about it, and answer listener questions from the audience.…

Build a Career in Data Science

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Chapter 14: Joining the Community 1:01:56

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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 when a data scientist starts to join the community.…

Build a Career in Data Science

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Chapter 13: Data Science Failures 1:06:00

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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 mistakes from her twisted deceptions.…

Build a Career in Data Science

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Chapter 12: Stakeholders 55:16

לפני 4 years55:16

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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 and Emily discuss how to make your stakeholders happy with good communication and empathy.…

Build a Career in Data Science

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Chapter 11: Data Science in Production 49:05

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Build a Career in Data Science

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Chapter 10: Making an Analysis 1:05:51

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Build a Career in Data Science

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Chapter 9: Starting a New Job 48:47

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Build a Career in Data Science

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Season 1 Intermission! 53:41

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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 new topic/technology. Finally, we talk about how to design good data science interviews as a hiring manager. Do we advocate for white boarding, take-homes, and unstructured interviews? Listen to hear our hot takes!…

Build a Career in Data Science

1
Chapter 8: Negotiating the Offer 55:57

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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’ll start your new job in the best way. Includes stories from Jacqueline and Emily's pasts!…

Build a Career in Data Science

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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 data science - analytics, decision science, and machine learning - and help you figure out which is best for YOU.…

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