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

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

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