Sr Data Scientist
Role details
Job location
Tech stack
Job description
We are looking for a Senior Data Scientist with strong classical ML expertise to design, build, and operationalize predictive models within the Microsoft Fabric ecosystem. You will work on high-impact use cases spanning demand forecasting, risk scoring, and anomaly detection for large-scale retail environments - translating raw data signals into actionable business intelligence., * Design and develop end-to-end classical ML pipelines - from feature engineering to model deployment and monitoring
- Build demand forecasting models leveraging external data signals (weather, events, seasonality) alongside historical sales data, at store/category/SKU level with 1 14 day horizons
- Develop ML-based risk scoring models across multiple fraud and exception scenarios, replacing manual rule-based processes with adaptive, dynamic thresholds
- Deliver daily prioritized outputs (investigation lists, inventory signals) that reduce detection and decision cycles from weeks to days
- Own model validation, threshold tuning, false positive reduction, and ongoing performance monitoring in production
- Collaborate with data engineers on feature pipelines using Microsoft Fabric Lakehouse, Dataflow Gen2, and OneLake
- Participate in iterative pilot-to-production delivery cycles with structured feedback incorporation
- Communicate model outputs and business impact clearly to both technical teams and business stakeholders
Requirements
Skills: Machine Learning, Azure Machine Learning, Artificial Intelligence, MLOps, AI Solution Architecture ,Microsoft Azure ,Microsoft Fabric, * 8 12 years of hands-on Data Science experience with a strong foundation in classical ML
- Proficiency in supervised and unsupervised ML techniques - gradient boosting, regression, classification, anomaly detection, time-series forecasting (XGBoost, LightGBM, scikit-learn, Prophet, statsmodels)
- Strong hands-on experience with Microsoft Fabric - ML Experiments, Notebooks (Python/PySpark), Lakehouse, Pipelines, and Dataflow Gen2
- Solid Python programming skills with experience building production-grade ML code
- Experience with MLflow for experiment tracking, model registry, and lifecycle management (native within Fabric)
- Proven experience building time-series forecasting models at granular levels (store, SKU, or category)
- Experience with anomaly detection and risk/fraud scoring models in retail or financial domains
- Strong skills in feature engineering, cross-validation, model interpretability (SHAP, LIME), and drift detection
Nice to Have:
- Experience integrating external data enrichment sources (weather APIs, economic indicators, third-party signals)
- Familiarity with retail loss prevention, exception-based reporting, or shrinkage analytics
- Exposure to Power BI or Fabric-native reporting for operationalizing model outputs to business users
- Knowledge of Azure ML and its relationship with Microsoft Fabric ML capabilities
- Experience with irregular or non-reorderable inventory environments
Benefits & conditions
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$18.00 per hour We want you to help us shape the future of shopping experiences and deliver on our purpose of connecting people with the products and experiences that enrich their lives. Joining S…
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26 days ago
*, + $18.00 per hour We want you to help us shape the future of shopping experiences and deliver on our purpose of connecting people with the products and experiences that enrich their lives. Joining S…
- 1 month ago
