Strata 2017 NYC - How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit
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The document discusses effective strategies for hiring data scientists by emphasizing the importance of intellectual sharpness and creativity over specific technical skills. It critiques unrealistic job requirements and suggests realistic expectations while clearly defining team goals. The text offers interview techniques, including the use of take-home tests, and stresses the importance of communication skills and problem-solving abilities in candidates.
Strata 2017 NYC - How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit
- 1. How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit 09/28/2017 Tanya Cashorali @TanyaCash21
- 2. 2004 201220072005 2006 20142013 2015 SPEAKER PROFILE TANYA CASHORALI @TANYACASH21 2
- 3. FIRST THINGS FIRST: WHAT IS A DATA SCIENTIST?
- 4. 2005 – R IS SCARY 4
- 5. Source: https://www.youtube.com/watch?v=2SQ0O_oPpe4 DATA SCIENTIST JOB POSTING 2008 Be challenged at LinkedIn. We’re looking for superb analytical minds of all levels to expand our small team that will build some of the most innovative products at LinkedIn No specific technical skills are required(we’ll help you learn SQL, Python, and R). You should be extremely intelligent, have quantitative background, and be able to learn quickly and work independently. This is the perfect job for someone who’s really smart, driven, and extremely skilled at creatively solving problems. You’ll learn statistics, data mining, programming, and product design, but you’ve gotta start with what we can’t teach –intellectual sharpness and creativity. 5
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- 16. STAHP, PLZ Recommend Reading: http://www.espn.com/nba/story/_/id/17678246/basic-concepts-not-math-heart-sports-analytics
- 17. UNREALISTIC REQUIREMENTS 39% of Data Scientist postings require an advanced degree Source: https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=IML14576USEN&
- 18. DEMAND > SUPPLY Maybe your hiring process is flawed?
- 19. DATA MATURITY PROGRESSION 19Source: https://www.americaninno.com/boston/startup-institute-and-stattleship-sports-data-science-and-analytics-class/ Huge Leap
- 20. WHAT SKILLS REALLY MATTER? 0% 10% 20% 30% 40% 50% 60% Knowledge of Algorithms Strong Statistical / Mathematical Skills Coding Efficiency (R/Python) Other - please describe Communication Skills Problem Solving / Curiosity What is the Most Important Attribute You Look for When Hiring a Data Scientist? Source: https://www.youtube.com/watch?time_continue=1287&v=I7IW9Z3h20Y 20
- 21. BUILD A TEAM THAT MEETS YOUR NEEDS Business/ Data Analyst Engineer Statistician Be realistic with your expectations Hire a great team instead of holding out for a unicorn Clearly define goals for your data team Understand the measures of success for the roles 21
- 22. INTERVIEW TECHNIQUES THAT WON’T CHASE AWAY YOUR CANDIDATES
- 23. WHITEBOARDING – THE WATERBOARDING OF TECH INTERVIEWS 23 Recommended Reading: https://medium.freecodecamp.org/why-is-hiring-broken-it-starts-at-the-whiteboard-34b088e5a5db https://medium.com/@evnowandforever/f-you-i-quit-hiring-is-broken-bb8f3a48d324
- 24. THE ON-SITE ALL DAY GAUNTLET 24Source: https://www.forbes.com/sites/susanadams/2014/04/16/how-to-survive-a-marathon-job-interview/#716e1178517b Don’t expect to eat at lunch. Though a company like Lending Club claims that lunch is a time for candidates to take a breather and relax, don’t. Your interviewers care about whether you are socially skilled and easy to be around. This is a good opportunity to ask questions. Query your dining companion about their career and how they like their employer. Remember that you are still being evaluated. You may not manage more than a few bites of food. Lierman recommends that you pack a small water bottle and snack in your bag which you can nibble when you excuse yourself to go to the restroom. Jot down notes when you take a bathroom break. Don’t take notes during a meal or in interviews. When you go to the rest room, jot down some points. These will come in handy when you follow up with thank-you notes. Pay particular attention to descriptions of the company’s challenges. You want to come off as a problem solver.
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- 26. CLEAR AND SIMPLE QUESTIONS 26 1.Which brewery produces the strongest beers by ABV%? 2.If you had to pick 3 beers to recommend using only this data, which would you pick? 3.Which of the factors (aroma, taste, appearance, palette) are most important in determining the overall quality of a beer? 4.Lastly, if I typically enjoy a beer due to its aroma and appearance, which beer style should I try? Dataset: https://s3.amazonaws.com/demo-datasets/beer_reviews.tar.gz
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- 28. ELEMENTS OF A SUCCESSFUL RESPONSE 28 Visualize & Communicate Summarize & Explore Aggregate & Manipulate
- 29. Reception to Feedback & Criticism Problem Solving & Writing Skills Communicate Findings COMPONENTS OF A SUCCESSFUL PRESENTATION 29
- 30. Aggregations and summary statistics should be expected, visualize and communicate results to the business More complex beer recommendation system, talk through a Bayesian approach.1 Communicate results to technical peers. Load the data into MongoDB or on Postgres RDS in the cloud, provide instructions to an analyst on how they can query the data. Communicate results to analyst team. 1. http://nbviewer.jupyter.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for- Hackers/blob/master/Chapter4_TheGreatestTheoremNeverTold/Ch4_LawOfLargeNumbers_PyMC2.ipynb TEST FOR THE ROLE (EXAMPLES) 30 Business/ Data Analyst Engineer Statistician
- 31. KEY TAKEAWAYS 31 Let’s be an inclusive and approachable field Let’s be more realistic about expectations Clearly define what you need Give this take-home test or something similar using your own data Have candidate present to the right team (interview only lasts 1 hour!)
- 32. SPECIAL THANKS TO… 32 Mara Averick @dataandme Oliver Keyes @kopshtik Renee Teate @BecomingDataSci Tom Neyarapally Jiggy Parikh
Editor's Notes
- #5: Printed out entire CRAN docs, that said I didn’t know ANYTHING, provided value with good mentors within a few months
- #6: So then what happened?
- #7: This happened
- #8: anyone here have a PhD in neurocomputing? AI?
- #9: Drew’s venn diagram within a venn diagram, accountant, head of IT
- #10: Art & Design, NLP, Mashups
- #14: And it got so bad DS themselves started making fun of them
- #18: Burning Glass mined its database of over 130 million unique current and historical job listings and worked with IBM and Business-Higher Education Forum (BHEF) to identify the key roles and skills that make up the DSA jobs ecosystem. First, Burning Glass identified a set of over 300 analytical skills that represent the key DSArelated tools and competencies requested in the labor market. These skills range from such general analytical competencies as database architecture, data analysis, and data visualization to specific technologies used to perform DSA-related tasks, such as R, Hadoop, and Tableau.
- #20: Huge talent gap, teaching experience. Are you developing algorithms? Understand the math? Just need applications?
- #24: Whiteboarding doesn’t work, humiliating and dehumanizing process
- #25: Whiteboarding doesn’t work, humiliating and dehumanizing process
- #26: Pick a real problem, if you don’t have one we will give you one, and it’s fun (beer!), This test can be given to PhD level data scientists or entry level data analysts, scales to find right fit based on your problems. Task the candidate with presenting their results to your team.
- #27: Open ended #2
- #28: same question, 4 different responses, all correct
- #30: Review the candidate’s coding and writing skills in their written results. This should reflect their ability to understand a question, use the right data to answer the question, and document their results to promote easy collaboration. Talk about example where guy communicated poorly Have them present these findings not only to the technical team, but also to executives if you expect this candidate to be presenting complicated results to business stakeholders. They should tailor their presentation accordingly. Be mindful of their ability to take feedback and constructive criticism from your team. Some candidates may be more defensive about their approach and not respond well to questions. This is a clear sign of someone that may be difficult to work with in a team-based environment.
- #31: These are just examples
- #32: You are a data scientist if you solve problems using data