Data Science is an evolving field, that requires a diverse skill set. From Analytical Techniques to Career Advice, this talk is full of practical tips that you can apply immediately to your job.

1. June 2–4, 2020
June 9–11, 2020
MACHINE LEARNING, AI,
AND DATA SCIENCE CONFERENCE

2. Tips & Tricks to
be an Effective
Data Scientist
Lisa Cohen

3. 3
Session goals
• Demystify Data Science Career Paths
• Discuss best practices to approach a Data Science Project
• Gain Tips & Tricks along the way!

4. Demystifying Career Paths
 Roles: What excites you about Data Science?
Data Scientist
Analytics & Inference
• Statistical analysis & experiments
Machine Learning 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

5. The Data Science Venn Diagram
 Technical
 Analytical Problem Solving
 Statistics
 Querying
 R, Python, SQL, Kusto
 Big Data
 Modeling
 Data Visualization
Technical
Soft
Skills
Business
 Business
 Business context
 Data sets
 Soft Skills
 Communication
 Organization
 Cross-Group Collaboration
 Teamwork
Conway’s Venn Diagram
Tip #2: Chart your path

6. 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

7. 7
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)

8. 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

9. 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

10. 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

11. Explore the underlying data
 Explore completeness, ranges, distributions
 Apply your sniff test
Tip #6: Unleash your curiosity

12. 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

13. Data Science in the real world
 Causation vs correlation
 Experiment considerations (opportunity cost, ethics, time to market)
 Done (and simple) are better than perfect
 Model explain-ability
 80/20 rule
 Skewed populations
 Value of data quality, monitoring and improving data sets
Tip #8: Prioritize practicality

14. Data Science
Lifecycle
Hypothesis
Problem
Framing
Data
Acquisition
&
Exploration
Analysis &
Predictive
Modeling
Evaluation &
Reviews
Deployment
&
Socialization
Data Science Lifecycle

15. 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

16. Simplify for Impact
 Quiz: Which one is better?
Tip #11: Eliminate Distractions

17. Leverage Libraries
Credit: Cole Nussbaumer Knaflic

18. 18
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
• Microsoft & Industry

19. Stay in Touch
https://www.linkedin.com/in/lisafeigenbaum/
https://medium.com/data-science-at-microsoft
Lisa.Cohen@microsoft.com

20. 20
Q&A

21. © Copyright Microsoft Corporation. All rights reserved.