Predictive Modeling
Churn prediction and demand forecasting
ML Model Deployment & Production Monitoring System
Deploy and monitor ML models in production with data-drift detection, concept-drift detection, performance tracking against ground truth, shadow deployment, and automated retraining triggers — with explicit SLOs for prediction latency, model accuracy, and drift thresholds.
Price Optimization Model & Elasticity Framework
Estimate price elasticity per SKU/segment using causal methods (not correlation), identify profit-maximizing prices via demand curves, and design A/B pricing experiments that produce trustworthy elasticity estimates — with guardrails for cannibalization and customer perception.
Time-Series Forecasting Framework & Model Selection System
A systematic framework for time-series forecasting that diagnoses series properties (stationarity, seasonality, trend) and selects the right method — ETS, ARIMA, Prophet, or ML — with walk-forward backtesting, prediction intervals, and decomposed residual analysis.
Fraud Detection Model & Real-Time Scoring System
Build fraud detection models that balance precision (false-positive cost) against recall (missed fraud cost) — using supervised scoring for known patterns, unsupervised anomaly detection for novel fraud, and feedback loops from chargeback/manual-review outcomes to continuously recalibrate.
Inventory Demand Forecasting & Replenishment System
Forecast SKU-level demand using time-series decomposition, seasonality, promotion uplift, and intermittent-demand methods (Croston/TSB) — with safety stock calculation tied to service-level targets and lead-time variability to prevent stockouts without overstocking.
Customer Lifetime Value (CLV) Prediction Model
Predict CLV per customer cohort and individual — using retention curves, expansion rates, and probabilistic modeling (BG/NBD + Gamma-Gamma for non-contractual, cohort survival for subscription) — to drive CAC caps, segmentation, and retention investment decisions.
Sales Forecasting Model & Pipeline Intelligence System
Build sales forecasts that beat rep gut-feel by wide margins — using pipeline velocity, stage conversion, seasonality, and rep-level calibration to produce weekly revenue predictions with confidence bands and commit vs. best-case tiers.
Predictive Lead Scoring & Conversion Probability Model
Design predictive lead scoring models that rank prospects by conversion probability — using firmographic, behavioral, and engagement signals to assign scores that tell sales teams which leads are most likely to buy, so effort is concentrated on the 20% of leads that generate 80% of revenue.
Demand Forecasting System & Inventory Optimization
Build demand forecasting systems that predict product demand with seasonality, trend, and external factors — to optimize inventory levels and reduce stockouts and overstock costs.
Churn Prediction Model & Retention Strategy
Build churn prediction models that identify at-risk customers before they leave — with feature engineering, model evaluation, and retention intervention strategies prioritized by customer value.