What is a Data Scientist
139 likes23,552 views
The document is a summary of a live Twitter chat featuring Dr. Michael Wu and Shanji Xiong discussing the role of data scientists, their needed skills, challenges, and industry trends. Key points include the importance of technical expertise, effective communication, and the necessity for companies to invest in data science for a competitive advantage. They also emphasize the evolving landscape of data science, including shifts from infrastructure to analytics and the specialization in various data-related domains.
What is a Data Scientist
- 1. #DataTalkWhat is a Data Scientist? LIVE TWEETCHAT FEATURING: Dr. Michael Wu Chief Scientist, Lithium @mich8elwu
- 2. Join our #DataTalk on Thursdays at 5 p.m. ET This week, we tweeted with Dr. Michael Wu, the Chief Scientist at Lithium, where he applies data-driven methodologies to investigate the complex dynamics of the social web. Check out all tweets from this Twitter chat: ex.pn/scientist
- 3. What type of work does a data scientist do?
- 4. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu âA data scientistâs work includes everything from data infrastructure (capture, store, process) to data service (retrieval). #DataTalk ex.pn/datatalk
- 5. Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong âA data scientist converts data into business intelligence. #DataTalk ex.pn/datatalk
- 6. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu âA data scientistâs work includes: decision science, business intelligence, customer analytics, marketing analytics, fraud, security, etc. #DataTalk ex.pn/datatalk
- 7. What are attributes of a good data scientist?
- 8. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu To be a data scientist, you need the technical expertise in computer science, statistics, and knowledge/experience with large data sets. #DataTalk ex.pn/datatalk â
- 9. Data scientists should have good intuition, strong coding capability, solid training in statistics & machine learning. #DataTalk ex.pn/datatalk â Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 10. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Educational background for data scientists can be computational genomics, astrophysicists, fluid dynamics, chemistry, biophysics (like me) ... #DataTalk ex.pn/datatalk â
- 11. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu To be a good data scientist, you need more than tech expertise. You must be a good communicator to explain complex data/analysis. #DataTalk ex.pn/datatalk â
- 12. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Good data scientists also need to be passionate about data. Iâd highly value curiosity, creativity and perseverance when hiring one. #DataTalk ex.pn/datatalk â
- 13. What kinds of companies have (or need) data scientists?
- 14. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Any company that already is invested in modern big data infrastructure will need data scientists to crunch the data. â ex.pn/datatalk #DataTalk
- 15. All companies need to have data scientists to stay competitive.â ex.pn/datatalk #DataTalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 16. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu All businesses use data, and data will grow so big that our brain and databases eventually canât handle ⌠they all need data scientists eventually. â ex.pn/datatalk #DataTalk
- 17. What types of teams do data scientists work with?
- 18. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu It all depends how the data organization is structured within the enterprise: independent team, hub & spoke, or silo in dept. ex.pn/datatalk â #DataTalk
- 19. Data scientists can work in R&D, product development and support business operations. ex.pn/datatalk â #DataTalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 20. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu SMBs use hub and spoke data teams where they report to different departments, but collaborate and work together, so data expertise is shared. ex.pn/datatalk â #DataTalk
- 21. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Large companies typically have entire teams of data scientists within each department and they usually donât collaborate. ex.pn/datatalk â #DataTalk
- 22. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Personally, I work internally with engineering, product, marketing, best practice, service, consulting, strategy, even sales and human resources. ex.pn/datatalk â #DataTalk
- 23. I process data, build models, engage with clients, and facilitate collaboration among Experian Data Labs. ex.pn/datatalk â #DataTalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 24. What are some big challenges that data scientists face?
- 25. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu One of the biggest challenges for data scientists is communication. Many data scientists speak tech & stats, but they donât speak business. â ex.pn/datatalk #DataTalk
- 26. Challenges for data scientists: data governance and what data can be used for â ex.pn/datatalk #DataTalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 27. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Other challenges for data scientists: Data access, data integration, and motivation.â ex.pn/datatalk #DataTalk
- 28. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu If a company is starting a data science initiative, their data scientist may not have access to all data due to security and compliance. â ex.pn/datatalk #DataTalk
- 29. Is there an art and science to working with big data?
- 30. Absolutely! Good intuition and domain knowledge are the keys for successful big data projects. â #DataTalk ex.pn/datatalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 31. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Thereâs definitely science to working with big data⌠there are rigorous stats and implementation details you learn from statistics and computer science. â #DataTalk ex.pn/datatalk
- 32. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Thereâs also art in working with big data, and this only comes with years of experience on working with big data. â #DataTalk ex.pn/datatalk
- 33. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Picking a good problem is sort of an art, choosing right features from an infinite number of features, too (feature engineering). â #DataTalk ex.pn/datatalk
- 34. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Exploratory data analysis (EDA): getting a feel or a hunch for how the data behaves is definitely an art. â #DataTalk ex.pn/datatalk
- 35. How can data scientists make a big impact in their business?
- 36. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu First, data scientists need to learn about the business, so they have the context to interpret the data and result of models/analyses. â #DataTalk ex.pn/datatalk
- 37. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Second, they need to pick a good problem: the most impactful problem that can be addressed with data they have access to. â #DataTalk ex.pn/datatalk
- 38. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Third, they must communicate effectively and make businesses understand the analysis and business implication of the insight they found. â #DataTalk ex.pn/datatalk
- 39. To be impactful, data scientists need to keep an open mind and concentrate efforts on most impactful problems. â #DataTalk ex.pn/datatalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 40. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu A good data scientist must be a good communicator, storyteller, teacher, etc. who can simplify complex data science for business. â #DataTalk ex.pn/datatalk
- 41. What are some big data trends?
- 42. Big data will be embraced by more and more businesses. More decisions will be driven by data and analytics. #DataTalk ex.pn/datatalk â Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 43. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu In past 5 years, most of the big data tech operate at the infrastructure layer. Now more people are focused on the algorithm layer. #DataTalk ex.pn/datatalk â
- 44. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu If thereâs a big data trend, itâs the shift from infrastructure to analytics/ algorithms on peopleâs big data asset. #DataTalk ex.pn/datatalk â
- 45. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu It used to be that data scientists can do everything about any data, now there is data engineering, algorithm, decision science. #DataTalk ex.pn/datatalk â
- 46. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Now thereâs experts in natural language processing, image analysis, video/audio processing, streaming data, etc. #DataTalk ex.pn/datatalk â
- 47. Why should companies invest more in data science?
- 48. Businesses invested in big data wisely will have a huge competitive advantage over their peers. â ex.pn/datatalk #DataTalk Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 49. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Companies should invest more in data science. They will need to eventually anyway.â ex.pn/datatalk #DataTalk
- 50. Any final tips for those who want to work in data science?
- 51. Tips for new data scientists: Keep an open mind, think outside the box, and work hard. The future is bright. #DataTalk ex.pn/datatalk â Shanji Xiong Global Chief Scientist, Experian @ShanjiXiong
- 52. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Final Tips: Learn the tech and stats, learn the business context, learn to communicate the tech/stats to business to bridge the gap #DataTalk ex.pn/datatalk â
- 53. Dr. Michael Wu Chief Scientist, Lithium @mich8elwu Be patient, follow your passion (which should be data), and pick a good problem to solve. #DataTalk ex.pn/datatalk â
- 54. Join our #DataTalk on Twitter on Thursdays at 5 p.m. ET. experian.com/datatalk