Tips for Effective Data Science in the Enterprise
1 like250 views
The document outlines best practices for effective data science within enterprises, focusing on career paths, project management, and community engagement. It emphasizes the importance of aligning passion with technical and soft skills, as well as prioritizing stakeholder communication and practicality in data projects. Tips are provided for various stages of the data science lifecycle, including project intake, model deployment, and career growth.
Tips for Effective Data Science in the Enterprise
- 1. Tips for Effective Data Science in the Enterprise Lisa Cohen
- 2. 2 Session goals • Demystify Data Science Career Paths • Discuss best practices to tackle a Data Science Project • Gain Tips & Tricks for DS scenarios in the enterprise
- 3. 2000 Applied Math Bachelor & Masters degrees Quantitative thinking, Applied sciences Cum laude 2004 VS Languages & IDE Technical Feature PM Building software, understanding customers, leading cross-functional feature team Incorporating SQL & data access into .NET programming languages Shipped VS 2005, 2008, 2010 Reached ~9M customers 3 patents for new designs 2012 Sr Mgr – VS Telemetry Product analytics: working with perf, compatibility, planning, privacy, compliance Led DevDiv business reviews, Advanced VS telemetry, Delivered VS active use clustering, Launched “Send A Smile” feedback 2015 Principal Data Scientist Mgr Using data to help customers succeed & grow on Azure. Driving DS best practices, Cross-MS partnerships Led cross-functional team. Evolved DS for credit offers, partners, Direct customers, Support. 2008 Sr Community PM - VS Divisional strategy, industry trends, Central org & systems, Cross group partners, Exec comms, CSAT & customer/ partner communities Led DevDiv blogs (3M+ views/mo), Presented keynotes & sessions at 50+ conferences YR Role Experience& Learnings Achievements
- 4. Nurturing customers, growing the business, connecting sources and advancing the DS craft Students & Developers Student offer, VSE Direct / Unmanaged Individuals, SMC, Sign-Up Field & EA Enable Sales Cross Cloud, Support, Retention, Service Usage, Fraud, Payments Data Science, Machine Learning, ML Ops, Experimentation, Data Vis, PM Partners & Startups ISVs, CSP, PAL, DPOR, MfS Marketplace App Source Partner Center Customer Portal Azure Portal Advisor Cost Management Azure.com Docs Learn PORTALSAUDIENCES FUNDA- MENTALS CAP- ABILITY
- 6. 6 Session goals • Demystify Data Science Career Paths • Discuss best practices to tackle a Data Science Project • Gain Tips & Tricks for DS scenarios in the enterprise
- 7. Demystifying Career Paths Roles: What excites you about Data Science? Data Scientist Analytics & Inference • Statistical analysis & experiments Machine Learning Scientist/Engineer Production Models • Develop predictive models, MLOps Data Engineer Data Platform & Pipelines • Build the data platform Program Manager Planning & Stakeholder Engagement • Manage the data science process Tip #1: Follow your passion
- 8. The Data Science Venn Diagram Technical Analytical Problem Solving Statistics Querying R, Python, SQL, Kusto Big Data Modeling Data Visualization Technical Soft Skills Domain Domain Business context Data sets Soft Skills Communication Organization Cross-Group Collaboration Teamwork Conway’s Venn Diagram Tip #2: Chart your path
- 9. Data Science Organizations What kind of environment do you want to be in? CentralizedEmbedded A core data science org provides services to business or functional teams across the company as a center of excellence Individual data science teams are spread throughout the company, reporting to and serving specific business or functional teams Tip #3: Find a DS community Tip #4: Connect with Stakeholders
- 10. 10 Project Intake Tips Kicking off a model, experiment or analytics project What new capability will this enable? What decision/action will you take? What’s the expected impact? Planning Process Project Intake Questions Prioritization & Scalable Solutions Tip #5: Focus on what matters (Prioritize with stakeholders, ask questions, socialize results)
- 11. Data Science Lifecycle Problem & Hypothesis Design Approach Data Acquisition & Exploration Analysis & Predictive Modeling Evaluation & Reviews Deployment & Socialization Data Science Lifecycle MS Doc: Team Data Science Process
- 12. Data Science Lifecycle Problem & Hypothesis Design Approach Data Acquisition & Exploration Analysis & Predictive Modeling Evaluation & Reviews Deployment & Socialization Data Science Lifecycle MS Doc: Team Data Science Process
- 13. Data Science Lifecycle Problem & Hypothesis Design Approach Data Acquisition & Exploration Analysis & Predictive Modeling Evaluation & Reviews Deployment & Socialization Data Science Lifecycle MS Doc: Team Data Science Process
- 14. Explore the underlying data Explore completeness, ranges, distributions Apply your sniff test Tip #6: Unleash your curiosity
- 15. Use engineering standards Make your work share-able & re-usable: Source Control & Notebooks Data dictionary Data contracts & SLAs Privacy, Compliance, Ethics Gather feedback to improve your results: Peer & Code reviews Office hours & brownbags Stakeholder presentation & action Publish Retrospectives Tip #7: Role model quality approaches
- 16. Data Science in the real world Causation vs correlation Experiment considerations (time to market, opportunity cost, ethics) Done (and simple) are better than perfect 80/20 rule Model explain-ability Skewed populations Value of data quality, monitoring and improving data sets Tip #8: Prioritize practicality
- 17. Data Science Lifecycle Problem & Hypothesis Problem Framing Data Acquisition & Exploration Analysis & Predictive Modeling Evaluation & Reviews Deployment & Socialization Data Science Lifecycle
- 18. Scientists must speak Presentation skills Be concise Focus on the takeaways Connect with your audience Use volume, eye contact, pauses Practice Tip #9: Land your message
- 19. Simplify for Impact Quiz: Which one is better? Tip #11: Eliminate Distractions
- 20. Leverage Libraries Credit: Cole Nussbaumer Knaflic
- 21. 21 Grow your career Hone your approach • Become a SME • Deliver results Increase your impact • Transform a space • Share new ideas • Help & represent the team Expand your horizons • Mentoring, Network • Books, Courses, Events • Company & Industry
- 23. 23 Q&A
- 24. © Copyright Microsoft Corporation. All rights reserved.
Editor's Notes
- #4: Careers are only built in retrospect You can’t connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future. You have to trust in something — your gut, destiny, life, karma, whatever. – Steve Jobs
- #6: Org maturity levels
- #8: Tips: Don’t feel limited by the boundaries Follow your passion and leverage your strengths Share your interests with your manager Take on projects that align with your future goals
- #9: Tips: Make a plan for career experiences & learnings Tackle Imposter Syndrome Apply the Venn diagram to the organization or Data Science field Notes: Leverage the diversity of the team backgrounds, with group projects Have fun with the team. Help & contribute to each other.
- #10: Pros/Cons & Tips: Pro: Drive product direction, product management Con/Tips: Join DS communities, Find a mentor Pro: More career paths, diverse projects, like-minded peers & team projects Con/Tips: Steering meetings, Joint planning, Join aliases for context, Find champs Notes: Grass is greener. All exist at Microsoft. MS is centralized at the product level
- #11: Data Science maturity stages Partner vs serving ad hocs, bring new ideas, file work Saying no, moving replies out of email, office hours
- #12: https://www.google.com/search?q=arc+arrow&tbm=isch&hl=en&chips=q:arc+arrow,g_1:blue:AlXoYtHtNkI%3D&rlz=1C1GCEU_enUS820US820&hl=en&ved=2ahUKEwjalJPLzfTpAhUzkZ4KHbMSAZIQ4lYoCHoECAEQJQ&biw=1479&bih=2261#imgrc=RX46V2bKlXmNmM&imgdii=wHBImvC5s7jK6M
- #15: https://unsplash.com/photos/M-EwSRl8BK8 Bring together end-to-end datasets Gain context from source owners
- #20: Use visual aids, make your message pop Make your visuals work for you, not against you
- #22: https://pixabay.com/photos/raise-challenge-landscape-mountain-3338589/
- #23: https://www.flaticon.com/free-icon/linkedin_174857 https://medium.com/@Medium