Lead the full development cycle of machine learning models, from prototyping and feature engineering to validation and deployment, ensuring scalable and production-ready solutions.
Apply statistical techniques such as A/B testing and back-testing, especially in imbalanced classification problems where precision and recall are critical.
Support strategic initiatives such as detecting property undervaluation, process automation, and the creation of predictive tools for new business verticals.
Translate complex findings into clear, actionable insights, delivering results to technical and non-technical audiences, including C-level stakeholders.
Act as mentor and technical guide for the Data Science team, reviewing code, setting standards, and fostering a collaborative, high-performing culture.

5+ years of experience delivering end-to-end machine learning solutions in production environments.
Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field.
A Master’s degree is a plus.
Advanced Python skills; proficient with Pandas, NumPy, scikit-learn, and Jupyter.
Strong hands-on PySpark and distributed data processing.
Strong understanding of supervised/unsupervised learning, deep learning, and ensemble methods.
Solid grounding in statistics, with real-world experience in imbalanced datasets.
Skilled in SQL; familiar with NoSQL systems.
Experience building visualizations and BI tools.
Proven ability to mentor and support junior team members.
Strong analytical thinking and problem-solving mindset.
Fluent in English; able to communicate assertively in technical and leadership contexts.
Confident presenter with experience addressing executives and cross-functional teams.

Senior Data Scientist

Key skills