Lead Data Scientist (Azure Databricks)
Anveta
- Tampa, Florida, United States
- Tampa, Florida, United States
À propos
applied ML CPG, FMCG Databricks Python pandas, PySpark, scikit-learn Experience with Azure ML or Azure ecosystem
Secondary Skills
MLOps & CI/CD for ML MLflow, GitHub Actions, or Azure DevOps pipelines to automate model retraining, evaluation gates, and deployment to Databricks Model Serving
Key Responsibilities
Lead end-to-end sales forecasting model development from data sourcing and feature engineering through model training, validation, and productionisation on Databricks (Azure) Design and maintain forecasting pipelines at SKU, category, and regional hierarchy levels incorporating POS data, promotional calendars, seasonality indices, and external signals (macroeconomic, weather) Apply CPG domain knowledge to model promotional uplift, new product introduction curves, product cannibalization, and retailer sell-in/sell-out dynamics into ML features and targets Operationalise ML models using MLflow on Databricks manage the model registry, version control experiments, automate retraining schedules, and configure drift monitoring alerts Collaborate with commercial and supply chain teams to translate forecast outputs into inventory recommendations, production planning inputs, and revenue growth strategies Define and enforce data science best practices modelling standards, experiment documentation, code review guidelines, and reproducibility requirements across the team Mentor junior data scientists conduct code reviews, lead knowledge-sharing sessions, support career development, and build a high-performance data science culture Communicate model insights and forecast accuracy to senior stakeholders through dashboards, executive briefings, and written reports making complex model behaviour accessible to business audiences Drive continuous model improvement benchmark new algorithms, evaluate AutoML approaches, and run controlled experiments to improve MAPE, bias, and coverage metrics Partner with data and platform engineers to ensure feature pipelines on Azure Data Lake / Delta Lake are reliable, scalable, and aligned with model refresh cadence requirements
Additional Requirements
Master's or PhD in Statistics, CS, or related field (preferred) Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps Provides regular updates, proactive and due diligent to carry out responsibilities
Communication & Interpersonal Skills
Communicate effectively with internal and customer stakeholders Communication approach: verbal, emails and instant messages Strong interpersonal skills to build and maintain productive relationships with team members Provide constructive feedback during code reviews and be open to receiving feedback on your own code Capability to troubleshoot and resolve issues efficiently
Compétences linguistiques
- English
Avis aux utilisateurs
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