Project Management Careers in Data Science
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This document discusses top career opportunities for project managers in data science. It outlines the typical roles and responsibilities of a data science project manager, including managing teams, translating business problems into data solutions, and driving organizational change and adoption of projects. The document emphasizes that while AI can perform many tasks, most organizations struggle to achieve business value from AI projects due to challenges like measuring impact. It provides tips for project managers to succeed in data science careers, such as learning both technical and domain skills, adapting frameworks to workflows, and owning change management.
Project Management Careers in Data Science
- 1. Top Data Science Career Opportunities For Project Managers Ganes Kesari September 28, 2022
- 2. 2 Senior Data Scientist Principal AI Storyteller Chief Data Wizard FEELING LUCKY? HERE’S A DATA SCIENCE TITLE GENERATOR! Data Statistical ML AI Chief Principal Senior Junior Associate Deputy Assistant Scientist Engineer Analyst Designer Developer Designer Storyteller Ninja Chef Wrangler Evangelist Rock Star Wizard Alchemist Vanity keywords Areas Activities
- 3. 3 BUZZWORDS AND BUSTED BUDGETS
- 4. 4 Build habits using data Love board games INTRODUCTION Ganes Kesari Co-founder & Chief Decision Scientist “Simplify Data Science for all” Present insights as stories on a low-code platform @kesaritweets /gkesari 100+ Clients | 250+ Team Backpacked solo in the Himalayas Innovation Titan Thought Leadership in data science Speak | Write | Consult
- 5. 5
- 6. 6 Art of the Possible with Data & Analytics
- 7. 7 THE JOURNEY FROM DATA TO DECISIONS Data Engineering Activity Phases Analytics | Data Science Decision Intelligence Data Collection Data Storage Data Transformation Reporting Insights Consumption Decisions Source: Article – When and how to build out your data science team
- 8. 8 THE JOURNEY FROM DATA TO DECISIONS Data Engineering Analytics | Data Science Data Collection Data Storage Data Transformation Reporting Insights Consumption Activity Phases Source: Article – When and how to build out your data science team Decision Intelligence Decisions
- 9. 9 REPORTING: HOW DID OUR SALES PERFORM? 2021 Boston Chicago Detroit New York Month Price Sales Price Sales Price Sales Price Sales Jan 10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58 Feb 8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76 Mar 13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71 Apr 9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84 May 11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47 Jun 14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04 Jul 6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25 Aug 4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50 Sep 12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56 Oct 7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91 Nov 5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89 Average 9.0 7.50 9.0 7.50 9.0 7.50 9.0 7.50 Variance 10.0 3.75 10.0 3.75 10.0 3.75 10.0 3.75 Sales numbers (in Mn) from four Cities Boston Chicago Detroit New York
- 10. 10 INSIGHTS - DESCRIPTIVE: WHEN ARE PEOPLE BORN IN THE US? Source: https://gramener.com/posters/Birthdays.pdf ..so, conceptions might happen here Very high births.. Love the Valentine’s? Too busy holidaying? Avoid April Fool’s Day? Unlucky 13th ? More births Fewer births
- 11. 11 More births INSIGHTS - DIAGNOSTIC: WHY ARE BIRTHS IN INDIA SO SKEWED? Source: https://gramener.com/posters/Birthdays.pdf Fewer births Most births in the first half A striking birth pattern seen on the 5th , 10th , 15th, 20th and 25th of each month… Very low births Aug onwards Why? Birthdates are ‘changed’ to aid early school admissions .. this is a typical indication of fraud!
- 12. 12 INSIGHTS - PREDICTIVE: IMPROVING CARGO HANDLING TURN TIMES https://gramener.com/cargo/
- 13. 13 CONSUMPTION: VISUALIZING NAPOLEON’S RUSSIAN CAMPAIGN http://en.wikipedia.org/wiki/File:Minard.png Charles Minard’s Flow Map
- 14. 14 What’s the deadliest animal in the world? DECISION INTELLIGENCE: SAVING MILLIONS OF LIVES WITH AI Source: WMP’s Wolbachia Method website; Geospatial AI to the rescue High Density of Wild Mosquitoes Low Density of Wild Mosquitoes
- 15. 15 The 6 Roles Every Data & Analytics Team Needs
- 16. 16 WHAT TEAM DO YOU NEED TO BUILD A DS SOLUTION LIKE THIS?
- 17. 17 HERE ARE THE BUILDING BLOCKS OF THIS EXAMPLE.. • Business workflow • Influencing factors • User journey • Visuals & aesthetics • Frontend/backend coding • Data pipelining • Impact analytics • Simulation algorithm • Piecing it all together • Change management • Data collection • Data transformation Domain Data Design Development Project Management Analytics
- 18. 18 ..AND THE 6 ROLES NEEDED TO DELIVER THEM Data Translator ML Engineer Data Engineer Information Designer Data Science Mgr Comic characters from Gramener Comicgen library Domain Data Design Development Project Mgmt • Domain expertise • Business analysis & Solutions • Software engineering • Front/back-end coding • Data sourcing & connection • Extract, load, transform • Information design • Interface/visual design • Business analysis • Team handling Data Scientist Analytics • Stats & ML • Scripting skills
- 19. 19 DATA SCIENCE PROJECT MANAGER 1. Work with the leadership to identify new initiatives 2. Translate business problems into data problems & solve them with a structured approach 3. Manage & mentor a team of D&A specialists 4. Story-tell business value from projects 5. Collaborate with teams across the firm 6. Drive organizational change management 7. Own and manage project portfolio /product roadmap 8. Tailor processes across the data science lifecycle 1. Strong business knowledge 2. Critical thinking and problem-solving 3. Basic, conceptual understanding of data engineering, data analytics, machine learning, information design and Dev Ops 4. Connect business and technology aspects 5. Good grasp of data science landscape 6. Exceptional interpersonal skills 7. Strong written, verbal & presentation skills Responsibilities Skills
- 20. 20 Why PMs are crucial for business value from AI
- 21. 21 AI CAN DO A LOT OF COOL THINGS TODAY… Monalisa - 80.LV ; Dal E 2 – Open AI; Midjourney –:NY TImes
- 22. 22 …BUT AI IS STRUGGLING TO DELIVER BUSINESS VALUE IN PROJECTS Source: PMI – Nasscom report 76% $11 Bn 7 of 10 of lost AI investment can be recovered with better PM practices of firms use their own custom methodologies for DS/AI projects organizations report minimal or no impact from AI projects
- 23. 23 TOP 3 CHALLENGES PMS ENCOUNTER IN DATA SCIENCE PROJECTS <> Data variability impacts scope & schedule Experimentation makes process adherence difficult Measuring and attributing success is tricky
- 24. 24 Secrets to Success in a Data Science PM Career
- 25. 25 #1: Learn non-core skills (D&A breadth + domain depth)
- 26. 26 #2: Embrace uncertainty and adapt frameworks for DS workflow
- 27. 27 #3: Own change management & drive business adoption
- 28. 28 TYPES OF PM ROLES IN THIS SPACE <> Potential Roles: Data Engineering Phases Analytics / Data Science Decision Intelligence Data Collection Data Storage Data Transformation Reporting Insights Consumption Decisions BI/Analytics Project Manager Data Engineering manager Data Science Technical PM Data Science Project Manager Data Science Product Manager
- 29. 29 IDENTIFYING YOUR NEXT PM ROLE IN DATA SCIENCE <> Hone business competency Build technology skills Network & scout for opportunities Track strategic data trends
- 30. 30 RECAP: HERE’S WHAT WE LEARNED TODAY • ROI from AI • High failure rate • Top challenges 3. Org value & AI • 3 Tips to success • Career options • Making the switch 4. Career Options • D&A Team • PM Responsibilities • PM Skills 2. 6 Roles in D&A • Insights • Consumption • Decisions 1. Art of the Possible
- 31. 31 “Ultimately, there's one investment that supersedes all others: Invest in yourself. - Warren Buffett Source: Quote rephrased from Predictably Irrational