[Hiring] Product Data Scientist @Solvd

Role Description

We are looking for a Product Data Scientist to partner closely with Credit Cards and Banking product teams, shaping product strategy and driving growth through rigorous analysis, experimentation, and applied machine learning.

You’ll work alongside Product Managers, Engineers, and business stakeholders to:

• Identify opportunities and influence product decisions.
• Measure the impact of new features — from optimizing how consumers discover and compare financial products to developing predictive tools such as approval odds and personalized recommendations.

This is a hands-on, highly analytical role for someone comfortable exploring complex data, challenging product assumptions, designing experiments, and translating insights into decisions that ship.

Qualifications

• 3+ years of professional experience in data science, product analytics, or a related analytical discipline — with demonstrated experience influencing product decisions through data.
• Strong proficiency in SQL and Python for data exploration, statistical analysis, automation, and predictive modeling.
• Hands-on experience with Databricks for analytical workflows, data processing, or model development — required.
• Proven experience designing, analyzing, and interpreting A/B tests, including statistical significance, power analysis, and common experimentation pitfalls.
• Strong understanding of product analytics — funnel optimization, metric development, cohort analysis, and behavioral segmentation.
• Working knowledge of applied statistics and machine learning techniques — regression, classification, propensity modeling, and/or causal inference.
• Experience developing dashboards and automating analytical workflows using modern BI and data tools.
• Excellent communication and collaboration skills — able to influence Product Managers, Engineers, and business stakeholders through data-backed recommendations.
• Bachelor’s or advanced degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related quantitative discipline, or equivalent practical experience.

Requirements

• Partner with Product Managers and vertical leadership to identify, size, and prioritize growth opportunities across the consumer journey.
• Establish metric frameworks — north-star metrics, funnel definitions, and performance drivers.
• Lead deep-dive analyses to understand consumer behavior, friction points, and performance trends.
• Translate ambiguous business questions into clear analytical approaches and actionable recommendations.
• Own the full experimentation lifecycle — hypothesis development, test design, statistical analysis, and business impact measurement.
• Develop predictive and statistical models that improve consumer experiences.
• Collaborate with Product and Engineering teams to translate findings into consumer-facing features.
• Use SQL, Python, Databricks, and BI tools to deliver analyses and reporting.
• Build and maintain metric definitions, dashboards, and measurement frameworks.
• Automate recurring analytical processes.
• Communicate findings clearly to both technical and non-technical stakeholders.
• Promote a data-driven product development culture across teams.

Benefits

• Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation.
• Be part of a global team with equal opportunities for collaboration across continents and cultures.
• Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.