causal inference , Sql, Python, difference-in-differences, MILP, uplift modelling, constrained optimisation, observational causal methods, optimising promotions, Lagrangian methods, synthetic control, instrumental variables, deep uplift architectures, propensity weighting, marketing incentives, heterogeneous treatment effect estimation, DR-learner, meta-learners, S T X R causal forests, Pricing

Orchestration, Sql, Nlp, Spark, Python, feature stores, LLMs, AI Agents, Time-series, Semantic Layer, MLflow, ML stack, anomaly detection, vector DBs, RAG, Recommenders, Knowledge Graphs

constrained optimization , causal inference , Sql, Python, difference-in-differences, MILP, Lagrangian methods, synthetic control, instrumental variables, propensity weighting, uplift modeling, heterogeneous treatment effect estimation

Dashboards, Data Quality, Data Governance, Python, Sql, analytics best practices, machine learning libraries, data visualisations

Tensorflow, Pytorch, Python, Machine Learning, Spark, Ray, reinforcement learning