Job Description

Key Responsibilities

• Analytical Solution Design: Translate ambiguous business challenges into structured analytical frameworks, defining data needs, modeling approaches, KPIs, and business success metrics for pilots and scalable deployments
• Advanced Modeling & Insights: Build, validate, and interpret predictive and prescriptive models (forecasting, pricing elasticity, segmentation, competitive analytics, digital shelf diagnostics) and convert results into clear business actions
• Scalable Pipelines & MLOps: Develop reproducible data and modeling pipelines; establish systems for data validation, model monitoring, drift detection, explainability, and refresh cycles across cloud environments
• Project Leadership: Guide 4–5 year analysts through problem-solving, technical execution, and quality assurance; ensure rigorous documentation, on-time delivery, and high-impact outcomes
• Stakeholder Engagement: Work closely with client teams in pricing, category management, merchandising, operations, and leadership to align on objectives, present insights, and influence decision-making

Required Skills

• Experience: 5+ years in advanced analytics, data science, or applied ML roles; consulting experience or multi-stakeholder environments preferred
• Technical: Strong proficiency in Python (Pandas, NumPy, scikit-learn), SQL, and experience with cloud platforms (Azure/AWS/GCP); solid understanding of model development, feature engineering, and pipeline scaling
• Analytical: Ability to hypothesize, test, interpret, and explain why performance or patterns emerge — not just what happened; strong grounding in statistical methods, experimentation, and ML
• Communication: Proven ability to present complex analytical concepts in simple, executive-ready language; capable of influencing senior clients and driving adoption of analytical solutions