[Remote] Senior Data Scientist / Analytical Lead (Part-Time) or Consultant
Note: The job is a remote job and is open to candidates in USA. TechSilo is seeking a Senior Data Scientist / Analytical Lead to analyze procurement, food, plastics, and emissions data from a public university system with more than 60 campuses. The role involves building and validating models, leading assigned Task Orders, guiding analysts, and communicating findings and limitations to non-technical leaders.
Responsibilities
- Design analyses of procurement, food, plastics, and emissions data collected by many campuses with different definitions and formats
- Build and validate forecasting, scenario, and benchmarking models, and state each model's horizon, assumptions, and uncertainty plainly
- Lead individual Task Orders when assigned: agree scope with the client, set the approach, track hours against the estimate, and report status
- Guide the analysts and dashboard developers on your team, and check methods before work goes to senior review
- Explain what the data does and does not show to campus and system leaders who are not data people
- Use AI-assisted tools only when the client approves them, document how they were used, and verify the results yourself
Skills
- Master's degree in data science, statistics, or a related field, or equivalent experience
- At least 8 years of professional experience in data science or advanced analytics
- Hands-on forecasting, statistical analysis, and scenario modeling in Python or R, plus SQL
- Experience preparing messy, inconsistent data from multiple sources into analysis-ready form
- Clear writing for non-technical readers, including honest statements of limits and uncertainty
- Experience with procurement or spend data, sustainability reporting, or emissions accounting (GHG Protocol, STARS)
- Work for a university, a public agency, or another organization made of many separate entities
- Experience leading several projects at once
- Familiarity with Power BI
Benefits
- Remote work
- You set your schedule within the delivery dates.
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