About this role
Job location: Remote About the role: We are looking for a skilled Data Scientist who can translate complex datasets into actionable business insights through rigorous statistical analysis and machine learning. The ideal candidate combines strong foundational knowledge of classical ML with a solid grasp of probabilistic and Bayesian modeling, and can operate effectively across the full spectrum from data exploration to production-ready model delivery. KEY RESPONSIBILITIES Design, build, and evaluate classical machine learning models for business-critical use cases (classification, regression, ranking, anomaly detection, time-series forecasting). Apply probabilistic and Bayesian modeling techniques to quantify uncertainty and inform decision-making under uncertainty; leverage tools like PyMC and PyMC-Marketing for Bayesian workflows. Perform rigorous EDA, feature engineering, and data wrangling on large structured and semi-structured datasets using Python and SQL. Collaborate with data engineers and analytics engineers to source, clean, and validate data pipelines feeding ML workflows. Develop, track, and communicate model performance metrics; identify degradation signals and recommend retraining or improvement strategies. Translate business questions into well-framed statistical problems and present findings clearly to technical and non-technical stakeholders. Maintain clean, reproducible, and well-documented code and notebooks following team engineering standards.