Senior Data Scientist

We are looking a Senior Data Scientist to join our data team and contribute to the design and delivery of high-impact analytical and modeling solutions. This role is suited for an experienced practitioner with a strong background in statistics, mathematical modeling, and applied machine learning, who can independently lead complex analytical initiatives and partner effectively with product and business teams.

The successful candidate will take ownership of end-to-end data science projects, from problem definition through deployment and evaluation, and will play an active role in shaping analytical standards and best practices across the organization.

Key Responsibilities

• Lead exploratory data analysis to identify patterns, risks, and opportunities relevant to product and business objectives.
• Design and apply appropriate statistical methods, hypothesis tests, and modeling techniques to address complex analytical questions.
• Develop, validate, and deploy predictive and statistical machine learning models in production environments.
• Translate business and product questions into well-defined analytical problems, metrics, and modeling approaches.
• Own the full lifecycle of data science projects, including methodology selection, implementation, validation, and impact assessment.
• Design, analyze, and interpret controlled experiments (e.g., A/B tests or randomized experiments) and communicate results to stakeholders.
• Build and maintain reliable data pipelines, analytical datasets, and reporting tools using Python.
• Review analytical work, provide technical guidance, and support the development of less-experienced team members.
• Contribute to the continuous improvement of data science processes, tools, and analytical rigor.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline. 
• At least 4 to 5 years of professional experience in data science, statistical analysis, or applied machine learning roles.
• Advanced proficiency in Python for data analysis, modeling, and visualization.
• Strong foundation in statistical inference, experimental design, and model evaluation techniques.
• Demonstrated ability to independently drive analytical projects in environments with incomplete or evolving requirements.
• Experience communicating analytical findings clearly and effectively to technical and non-technical stakeholders.
• Strong collaboration skills and a high standard of analytical quality and documentation.

Preferred Qualifications:

• Experience with advanced mathematical or probabilistic modeling.
• Demonstrated experience designing and analyzing randomized controlled experiments.
• Familiarity with recommender systems or personalization problems.
• Experience with adaptive experimentation methods, such as multi-armed bandits.