statistical concepts , probability , Tableau, Sql, Clustering, Python, Sap Business Objects, R, R-Shiny, Microstrategy, Looker, regressions

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

Machine Learning, Artificial Intelligence, Scala, Deep Learning, Tensorflow, Pytorch, Spark, Information Retrieval, Python, Sequence Modelling, Representation Learning, User Modelling, Recommendation Systems, Transformers

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, MILP, difference-in-differences, instrumental variables, uplift modeling, synthetic control, propensity weighting, heterogeneous treatment effect estimation, Lagrangian methods

, MLops, Cloud Architecture, Software Development, Machine Learning, Open Source Libraries, Ai