Senior Product Data Scientist

As a Senior Product Data Scientist, you’ll work as part of a cross-functional team alongside product managers, designers, and software and analytics engineers, using data and your expertise to influence and drive the strategy of our products. You’ll help define how we measure the success of our products, collaborate with engineers on how we collect data, design and help build reports/dashboards, and run analyses to find product improvement opportunities. You’ll be a co-owner of a product, driving it to success in partnership with other cross-functional team members. Data Analytics at Checkout.com is a highly visible function that critically impacts the company’s success. It underpins our business plans and forms the basis for how we set our company objectives. As a leader in this group, you’ll have a wider support network of Analytics Engineers, Product Data Scientists, and Data Product Managers., * You’ll be responsible for driving analytics of a product pillar.

• You’ll lead a team that defines, measures, and presents metrics, delivering actionable insights.
• Contribute product roadmaps through data-based recommendations and continuously define high-impact areas for improvement.
• Work closely with Data Analytics Engineers and Software Engineers to make sure we collect and model the right data to produce relevant business insights.
• Foster data culture across products and technology by actively sharing insights and ideas and building positive relationships with colleagues.
• Build experiments and analysis frameworks to quantify the ROI of product development.
• Lead by example, guiding your team and the broader data community to apply best practices in analytics from data collection to analysis.

• Strong communicator, able to explain complex technical topics to non-technical team members.
• Experience conducting experiments, building measurement frameworks, and validating the results with relevant quantitative methods.
• Strong analytical mind and demonstrable experience in converting ambiguous problems into structured and data-informed solutions.
• Excellent data interrogation skills with SQL.
• Knowledge of applied statistics (e.g., hypothesis testing, regression).