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How to Hire and Test for Data Skills:
A One-Size-Fits-All Interview Kit
09/28/2017
Tanya Cashorali
@TanyaCash21
2004 201220072005 2006 20142013 2015
SPEAKER PROFILE
TANYA CASHORALI
@TANYACASH21
2
FIRST THINGS FIRST:
WHAT IS A DATA SCIENTIST?
2005 – R IS SCARY
4
Source: https://www.youtube.com/watch?v=2SQ0O_oPpe4
DATA SCIENTIST JOB POSTING 2008
Be challenged at LinkedIn. We’re looki...
#BLAMEDREWCONWAY
6
7
8
9
10
11
12
Source: https://ironholds.org/arbitrary-things/
JOB DESCRIPTIONS NOW
STAHP, PLZ
Recommend Reading: http://www.espn.com/nba/story/_/id/17678246/basic-concepts-not-math-heart-sports-analytics
UNREALISTIC REQUIREMENTS
39% of Data Scientist
postings require an
advanced degree
Source: https://www-01.ibm.com/common/s...
DEMAND > SUPPLY
Maybe your hiring
process is flawed?
DATA MATURITY PROGRESSION
19Source: https://www.americaninno.com/boston/startup-institute-and-stattleship-sports-data-scie...
WHAT SKILLS REALLY MATTER?
0% 10% 20% 30% 40% 50% 60%
Knowledge of Algorithms
Strong Statistical / Mathematical Skills
Cod...
BUILD A TEAM THAT MEETS YOUR NEEDS
Business/
Data Analyst
Engineer Statistician
 Be realistic with your
expectations
 Hi...
INTERVIEW TECHNIQUES THAT
WON’T CHASE AWAY
YOUR CANDIDATES
WHITEBOARDING – THE WATERBOARDING OF TECH INTERVIEWS
23
Recommended Reading:
https://medium.freecodecamp.org/why-is-hiring...
THE ON-SITE ALL DAY GAUNTLET
24Source: https://www.forbes.com/sites/susanadams/2014/04/16/how-to-survive-a-marathon-job-in...
25
CLEAR AND SIMPLE QUESTIONS
26
1.Which brewery produces the strongest beers by ABV%?
2.If you had to pick 3 beers to recomm...
27
ELEMENTS OF A SUCCESSFUL RESPONSE
28
Visualize &
Communicate
Summarize &
Explore
Aggregate &
Manipulate
Reception to
Feedback &
Criticism
Problem Solving &
Writing Skills
Communicate
Findings
COMPONENTS OF A SUCCESSFUL PRESENT...
Aggregations and summary statistics should be expected, visualize
and communicate results to the business
More complex bee...
KEY TAKEAWAYS
31
 Let’s be an inclusive and approachable field
 Let’s be more realistic about expectations
 Clearly def...
SPECIAL THANKS TO…
32
Mara Averick
@dataandme
Oliver Keyes
@kopshtik
Renee Teate
@BecomingDataSci
Tom Neyarapally Jiggy Pa...
Strata 2017 NYC - How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit
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Strata 2017 NYC - How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit

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Most people agree that interviewing is one of the most difficult and least enjoyable professional activities. Given the recent demand for data analytics and data science skills, it has become an increasingly daunting task for managers to adequately test and qualify candidates.

Interviewing hundreds of individuals of varying backgrounds requires a more efficient way of quantifying technical and cultural fit. This demand led to the creation of a deceptively simple data exercise, which reveals a surprising amount of information about interviewees. This test has been administered to dozens of candidates of varying experience levels and formal backgrounds. Data science is a highly integrated discipline. The variance in solutions provided by a physicist compared to a computer scientist is fascinating.

Tanya Cashorali digs deeper into these approaches and provides recommendations on how to administer and review test results for each type of candidate. You’ll receive a link to the publicly available dataset, the test questions, and the scoring rubric and learn how to save time vetting candidates, move away from unrealistic whiteboarding interviews, and start hiring data scientists who will quickly provide business value.

Published in: Technology
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Strata 2017 NYC - How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit

  1. 1. How to Hire and Test for Data Skills: A One-Size-Fits-All Interview Kit 09/28/2017 Tanya Cashorali @TanyaCash21
  2. 2. 2004 201220072005 2006 20142013 2015 SPEAKER PROFILE TANYA CASHORALI @TANYACASH21 2
  3. 3. FIRST THINGS FIRST: WHAT IS A DATA SCIENTIST?
  4. 4. 2005 – R IS SCARY 4
  5. 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
  6. 6. #BLAMEDREWCONWAY 6
  7. 7. 7
  8. 8. 8
  9. 9. 9
  10. 10. 10
  11. 11. 11
  12. 12. 12
  13. 13. Source: https://ironholds.org/arbitrary-things/
  14. 14. JOB DESCRIPTIONS NOW
  15. 15. STAHP, PLZ Recommend Reading: http://www.espn.com/nba/story/_/id/17678246/basic-concepts-not-math-heart-sports-analytics
  16. 16. UNREALISTIC REQUIREMENTS 39% of Data Scientist postings require an advanced degree Source: https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=IML14576USEN&
  17. 17. DEMAND > SUPPLY Maybe your hiring process is flawed?
  18. 18. DATA MATURITY PROGRESSION 19Source: https://www.americaninno.com/boston/startup-institute-and-stattleship-sports-data-science-and-analytics-class/ Huge Leap
  19. 19. 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
  20. 20. 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
  21. 21. INTERVIEW TECHNIQUES THAT WON’T CHASE AWAY YOUR CANDIDATES
  22. 22. 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
  23. 23. 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.
  24. 24. 25
  25. 25. 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
  26. 26. 27
  27. 27. ELEMENTS OF A SUCCESSFUL RESPONSE 28 Visualize & Communicate Summarize & Explore Aggregate & Manipulate
  28. 28. Reception to Feedback & Criticism Problem Solving & Writing Skills Communicate Findings COMPONENTS OF A SUCCESSFUL PRESENTATION 29
  29. 29. 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
  30. 30. 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!)
  31. 31. SPECIAL THANKS TO… 32 Mara Averick @dataandme Oliver Keyes @kopshtik Renee Teate @BecomingDataSci Tom Neyarapally Jiggy Parikh

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