Reemu
Senior Data Scientist
Bengaluru, India · UTC+5:30 · 13 years of experience
Reemu focuses on turning messy data into tested models and useful decisions.
Request a shortlistWhy this profile fits
Decision-first problem framing
Starts with the decision, target metric, and data limits before choosing a model or analytical method.
Validated modeling
Uses holdouts, experiment design, and error analysis to separate a useful signal from a convincing notebook.
Clear operational handoff
Documents assumptions, monitoring needs, and the path from analysis to a decision or production workflow.
Relevant toolkit
PythonSQL
scikit-learn
PyTorch
dbtDelivery evidence
Selected work
Hierarchical Demand Forecasting Platform
National grocery retailerReplaced a manual SARIMAX process with a reconciled hierarchical LightGBM forecast across 40,000 SKUs and 1,200 stores. Cut weighted error from 31% to 18% and freed roughly $9M in working capital while lowering fresh-food waste by 22% within two quarters.
Probabilistic Sales Forecasting for S&OP
Consumer packaged goods manufacturerBuilt a Temporal Fusion Transformer producing P10/P50/P90 sales forecasts feeding a monthly sales-and-operations planning cycle. Improved 13-week forecast bias from 12% to under 3% and gave finance defensible revenue ranges, cutting emergency production runs by a third.
Relevant experience
Career timeline
Principal Data Scientist, Forecasting
2021–PresentDevlyn (a ViitorCloud company) · Bengaluru, India (Remote)
- Lead demand and sales forecasting engagements for retail, CPG, and logistics clients, owning models from data contract to production and typically improving forecast accuracy 20% to 40% within the first quarter.
Software Engineer
Sep 2022–PresentViitorCloud Technologies · Bengaluru, India
- Built the first end-to-end demand forecasting system for a national grocery client, moving 40,000 SKUs off spreadsheets onto hierarchical LightGBM and freeing about $9M in working capital.
Full Stack Developer Intern
Jan 2022–Sep 2022iView Labs Pvt. Ltd. · Bengaluru, India
- Developed weekly sales forecasts for 5,000+ product categories that fed inventory and marketing budgets, improving category-level accuracy 18% over the incumbent moving-average model.
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Skill depth
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Relevant experience by skill
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Languages
Frameworks
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Tools
Paradigms
Platforms
Storage
Other
Education
Formal background
Master of Statistics (M.Stat), Statistics
Indian Statistical Institute · 2011–2013 · Specialization in time-series analysis and applied statistics
Bachelor of Science (B.Sc), Statistics
University of Delhi · 2008–2011 · First class with distinction
Credentials
Certifications
SnowPro Advanced: Data Scientist
Snowflake · 2024 · Certified
AWS Certified Machine Learning Engineer – Associate
Amazon Web Services · 2023 · Certified
Communication
Languages
Tamil
Native
Hindi
Fluent
English
Fluent
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