Senior Data Scientist

About the role.

We are seeking a talented and experienced Senior Data Scientist to join our team, focusing on developing and optimising advanced models that support a wide range of business needs - from product personalisation initiatives to driving growth opportunities. You will work with diverse data sources to enhance user experience and improve operational efficiency across the business. This role involves close collaboration with cross-functional teams, including product managers, engineers, and other data scientists, to ensure that data-driven insights are effectively integrated into product strategies and broader business growth initiatives.

Day-to-day responsibilities.

• Work with large, complex datasets to solve a wide range of challenging problems using diverse analytical and statistical approaches.
• Apply technical expertise in quantitative analysis, experimentation, data mining, and data presentation to develop strategies for products serving millions of customers and thousands of merchants.
• Present complex data science findings and methodologies to senior stakeholders in a clear and concise way.
• Apply machine learning methods to solve product-related business problems and improve decision-making processes.
• Contribute to the team’s coding efforts, ensuring best practices in version control and model deployment.
• Use Python and core machine learning libraries to build, validate, and deploy models.
• Conduct A/B testing and experimental analyses to evaluate new features and product changes.
• Support continuous improvement of team methodologies, workflows, and tooling.

What we’re looking for.

• Several years of hands-on experience as a data scientist, with a focus on building and deploying models that enhance customer product experiences.
• Proficiency in SQL, Python, and core data science and machine learning libraries (e.g., NumPy, Pandas, Scikit-Learn).
• Experience communicating complex ideas to non-technical audiences and senior stakeholders.
• Strong understanding of machine learning methods, real-world application, and awareness of their limitations.
• Experience with version control systems (e.g., Git) and the ability to collaborate in multi-developer environments.
• Results-driven mindset with the ability to iterate quickly and improve models in production.
• Knowledge of AI safety considerations, including bias detection, privacy management, and handling of personally identifiable information (PII).

Bonus Skills.

• Experience using Amazon SageMaker for model development and deployment.
• Familiarity with software development best practices and CI/CD pipelines (e.g., GitHub Actions).
• Experience monitoring machine learning model performance.
• Knowledge of cloud-based model training, archiving, and serving solutions, including endpoint deployment.
• Experience using DBT for data modelling and Looker for BI reporting.
• Interest in staying up to date with evolving technologies and applying them to improve business outcomes.