Lead Data Scientist

Roles and Responsibility

• Work experience of years of experience in applied data science, analytics, or ML engineering.
• Strong math or statistics background, specifically strong grasp of descriptive and probabilistic theories, sampling.
• Strong analytic and problem-solving skills, understanding and experience in application of AI methodologies for data manipulation and insight.
• Experience in building and execution of advanced solutions for audience analytics and insights.
• Strong SQL skills and comfort working with large-scale, multi-source data.
• Experience with version control (Git) and collaborative coding workflows.
• Advanced Python skills, incl. pandas, Numpy, scikit-learn, SciPy, stats models for modelling and analytics.
• Solid understanding of predictive modelling, feature selection, and model evaluation (AUC, lift, calibration, etc.).
• Experience with gradient boosting methods (xgboost, lightgbm, or cat boost).
• Experience with Power BI or other data visualization tools especially geo coded data is a big plus.
• Sufficient knowledge of data governance practices including data QA, general naming taxonomy, data & platform integration, etc.
• Ability to foster collaborative relationships with cross-functional team.
• Excellent written, oral, and presentation communication.
• Ability to communicate analytical findings to non-technical stakeholders clearly and impactfully.

Preferred candidate profile