Podcast
Solo Data Scientist Playbook: 90-Day Roadmap, Pipelines, A/B Tests & Prioritization
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Solo Data Scientist Playbook: 90-Day Roadmap, Pipelines, A/B Tests & Prioritization
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Episode Overview
How can a solo data scientist deliver measurable impact in the first 90 days? In this episode, Marianna Diachuk — data scientist at Restream, former DataRobot engineer and fintech team lead, and Data Science Lead/mentor with Women Who Code — walks through a practical Solo Data Scientist playbook. You’‘ll hear a clear 90-day roadmap covering first-week stakeholder interviews and data exploration, first-month research and proofs-of-concept, and first-quarter priorities: building data pipelines, deployment,.
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Chapter Summary
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- 0:00 - Podcast Introduction
- 0:02 - Guest Background & Career Path in Data Science
- 3:42 - Solo Data Scientist: Freedom, Influence & Responsibility
- 8:13 - Company Prerequisites: Data Pipelines, Engineers & Analytics
- 10:53 - Experience Required: Mid-Senior, End-to-End Project Skills
- 12:33 - Problem Discovery: Translating Business Needs to Data Science
- 14:25 - Proactive Outreach & Building a Data Science Roadmap
- 16:01 - Prioritization: Feasibility, Impact & Stakeholder Alignment
- 21:07 - First Week: Stakeholder Interviews and Data Exploration
- 22:25 - First Month: Early Research, Insights or Proof-of-Concept
- 24:07 - First Quarter: Pipelines, Methodology, Deployment & A/B Testing
- 25:40 - Managing Expectations: Data Science as Iterative Inquiry
- 28:07 - Start Small: Exploratory Analysis, Dashboards vs. Machine Learning
- 30:11 - Churn Workflows: Analysis to Model to Marketing Collaboration
- 32:54 - Project Timelines: Reuse, Automation & Faster Iterations
- 34:23 - Solution Selection: Define Metrics and Measure Outcomes
- 35:49 - Evaluating Performance: KPIs, Experiments & Delivering Insights
- 39:25 - When You Get Stuck: Networks, Communities & Learning Resources
- 40:59 - Communicating Results: Reports, Visualizations & Tech Talks
- 43:56 - Transitioning from Engineering: Mindset, Deployment & Monitoring
- 45:47 - Scaling the Team: Signals to Hire More Data Scientists
- 48:02 - Stopping Projects: Prioritize, Cut Losses & Reallocate Effort
- 50:17 - Interview Checklist: Questions to Assess Company Readiness
- 54:15 - Assessing Readiness: Pipelines, Analytics Dept. & Expectations
- 55:18 - Research to Production: Silent Mode, A/B Tests & Safe Rollout
- 57:15 - Closing Advice: Learn Fast and Educate Your Organization
- 57:52 - Contact Info & Episode Wrap-up