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Getting Plugged Into Data Science

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Slides from the Dallas Data Science Conferences (by IDEAS)

Published in: Data & Analytics
  • People think that you have to get 'academically advised' in this area. Truth is I have been straddling between academics and getting out there for experience of FDA and USDA Projects. You need people who have advanced degrees, some with advanced degrees with considerable experience and really senior people who have been through some battles. Walter Earl Roper, Arboretum, Austin, TX, roperw4@gmail.com, roeprw@uisalumni.org
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  • Hey Caitlin, I had similar ideas of building my own brand with my work but never knew if my thoughts are in the right direction. Your session helped me in becoming sure of my thougths and gave me the direction I was looking for! Thanks a lot for such a wonderful presentation!
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Getting Plugged Into Data Science

  1. 1. GETTING PLUGGED INTO DATA SCIENCE Caitlin Hudon | Data Scientist @ Web.com @beeonaposy
  2. 2. MY DEFINITION OF “PLUGGED IN” + Being involved + Putting yourself out there + Sharing your experiences + Caring about the field beyond the work
  3. 3. WHY GET PLUGGED IN? + Helps (a lot) with getting jobs + Build a network of friends + Open up new resources for growth + Speaking invitations + Build your personal brand
  4. 4. BEING PLUGGED IN HELPS YOU STAND OUT
  5. 5. GETTING PLUGGED IN STAYING PLUGGED IN
  6. 6. 4. Beating imposter syndrome 5. Giving back to the community 1. Building your network 2. Developing underrated skills 3. Helping employers find you
  7. 7. Source: giphy
  8. 8. NETWORKING IS AWKWARD Source: giphy
  9. 9. THINK OF NETWORKING AS FINDING YOUR PEOPLE
  10. 10. AND CONNECTING WITH THEM
  11. 11. Source CONFERENCES
  12. 12. JOIN GROUPS (like R-Ladies!)
  13. 13. HAPPY HOURS
  14. 14. WORKSHOPS
  15. 15. #pydata #rstats #datascience TWITTER Source: giphy
  16. 16. HACKATHONS Source: giphy
  17. 17. BOOK CLUBS
  18. 18. 4. Beating imposter syndrome 5. Giving back to the community 1. Building your network 2. Developing underrated skills 3. Helping employers find you
  19. 19. UNDERRATED SKILLS
  20. 20. COMMUNICATION
  21. 21. SQL
  22. 22. DATA MUNGING
  23. 23. BUSINESS CONTEXT Business Question Data Question Business Answer Data Answer
  24. 24. 4. Beating imposter syndrome 5. Giving back to the community 1. Building your network 2. Developing underrated skills 3. Helping employers find you
  25. 25. MEETUPS Source: tweet by Steph Locke GITHUB PROFILE
  26. 26. MEETUPS Source PROJECT PORTFOLIO
  27. 27. Source: Emily Robinson’s website BLOG / WEBSITE
  28. 28. TWITTER + Live-tweet conferences + Find cool blog entries + Keep up with DS news + Build your network + Share your projects
  29. 29. I’m interviewing for your former position at Company A. I saw that you’re at Company B now. It looks like our backgrounds are similar (and we have similar interests -- I applied at Company B too). I’d love to hear any advice you have about working in Austin’s data scene. I’m glad you reached out to me. What job did you apply for at Company B? We have a Sr. Marketing Data Analyst job on my team that seems like a good fit for you. I’ll do my best to get you an interview for it. LINKEDIN
  30. 30. 4. Beating imposter syndrome 5. Giving back to the community 1. Building your network 2. Developing underrated skills 3. Helping employers find you
  31. 31. IMPOSTER SYNDROME “A false and sometimes crippling belief that one's successes are the product of luck or fraud rather than skill”
  32. 32. DATA SCIENCE IS A NEW FIELD “Business analyst” “Data analyst” “Research scientist”
  33. 33. DATA SCIENCE IS A COMBINATION OF OTHER FIELDS + Data analysis + Statistics + Software engineering + Machine learning + Visualization + Database administration + Business acumen Source: Machine Learning 101 deck
  34. 34. DATA SCIENCE IS CONSTANTLY EXPANDING
  35. 35. DATA SCIENCE IS CONSTANTLY EXPANDING
  36. 36. DATA SCIENCE IS CONSTANTLY EXPANDING
  37. 37. DATA SCIENCE IS CONSTANTLY EXPANDING
  38. 38. DATA SCIENCE IS CONSTANTLY EXPANDING
  39. 39. x Source: Hugh Kearns’ tweet
  40. 40. MY APPROACH I will never be able to learn everything there is to know in data science — I will never know every algorithm, every technology, every cool package, or even every language — and that’s okay.
  41. 41. 4. Beating imposter syndrome 5. Giving back to the community 1. Building your network 2. Developing underrated skills 3. Helping employers find you
  42. 42. GIVE A TALK + Start local + Lightning talks + Beginner-level is great!
  43. 43. THINK OPEN SOURCE + Help the next person + Contribute to OS projects + Share your work
  44. 44. KEEP BLOGGING + Audience: you, 2 weeks ago + Tracking your learning → #DSlearnings + Share what’s helped you
  45. 45. RESOURCES: GETTING PLUGGED IN + Building your data science network (finding community and reaching out), [Emily Robinson] + Questions to ask in interviews [Julia Evans] + Making peace with personal branding [Rachel Thomas] + How to build your personal brand as a new web developer [Rick West]
  46. 46. RESOURCES: STAYING PLUGGED IN + Learning at work [Julia Evans] + Contributing to open source [Julia Evans] + Advice to aspiring data scientists: start a blog [Dave Robinson]
  47. 47. THANK YOU! Caitlin Hudon @beeonaposy caitlinhudon.com Slides: github.com/caitlinhudon/dallas_data_science

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