Python Data Scientist | Energy & Trading Analytics | Forecasting, Decision Systems & Dashboards I build production-grade analytics that turn data into clear, risk-aware decisions—forecasting, anomaly detection, calibrated thresholds, and dashboards teams actually use. Background in front-office power trading, with strong focus on validation, monitoring, and data-quality controls. I’m a Python/SQL data scientist specialising in time-series forecasting and decision-support systems, with a strong edge in energy and trading analytics. I don’t stop at “building a model”—I deliver usable outputs: dashboards, alerts, calibrated decision rules, and reproducible pipelines with validation and monitoring built in. I’m experienced translating statistical signals into practical execution frameworks (guardrails, thresholds, checklists) that hold up under changing regimes. Typical engagements include rapid scoping and success-metric definition, a working prototype in week one, and iterative delivery with clean documentation and handover so your team can run and maintain the solution. #Services * Time-series forecasting pipelines (feature engineering, backtesting, drift monitoring) * Anomaly detection / outlier & regime monitoring * Decision rules & alerting (threshold calibration, guardrails, QA checks) * Analytics dashboards (e.g., Streamlit/Dash) and reporting packs * Data pipelines (Python + SQL): cleaning, QA, documentation, handover #Keywords Python, SQL, time series, forecasting, anomaly detection, monitoring, dashboards, data pipeline, backtesting, decision rules, energy markets, power trading, market microstructure…Python Data Scientist | Energy & Trading Analytics | Forecasting, Decision Systems & Dashboards I build production-grade analytics that turn data into clear, risk-aware decisions—forecasting, anomaly detection, calibrated thresholds, and dashboards teams actually use. Background in front-office power trading, with strong focus on validation, monitoring, and data-quality controls. I’m a Python/SQL data scientist specialising in time-series forecasting and decision-support systems, with a strong edge in energy and trading analytics. I don’t stop at “building a model”—I deliver usable outputs: dashboards, alerts, calibrated decision rules, and reproducible pipelines with validation and monitoring built in. I’m experienced translating statistical signals into practical execution frameworks (guardrails, thresholds, checklists) that hold up under changing regimes. Typical engagements include rapid scoping and success-metric definition, a working prototype in week one, and iterative delivery with clean documentation and handover so your team can run and maintain the solution. #Services * Time-series forecasting pipelines (feature engineering, backtesting, drift monitoring) * Anomaly detection / outlier & regime monitoring * Decision rules & alerting (threshold calibration, guardrails, QA checks) * Analytics dashboards (e.g., Streamlit/Dash) and reporting packs * Data pipelines (Python + SQL): cleaning, QA, documentation, handover #Keywords Python, SQL, time series, forecasting, anomaly detection, monitoring, dashboards, data pipeline, backtesting, decision rules, energy markets, power trading, market microstructureWWWW…