Senior Data Scientist - Product

What You’ll Do

• Translate business needs into data analysis and actionable insights to optimize product performance and user experience for both existing and new products.
• Work closely with product managers, engineers, and other cross-functional stakeholders to identify critical product questions and provide data-driven solutions.
• Develop and maintain a scalable, reliable, and accurate analytics infrastructure to support product decisions.
• Establish and maintain best practices for data collection, analysis, and reporting.
• Deliver actionable insights and recommendations focused on landing tangible product impact.
• Help foster a culture of data-driven decision-making and continuous improvement within the product teams.
• Ensure the integrity and accuracy of the data used for analysis and reporting.
• While the primary focus is on existing products, support 0 to 1 product launches by identifying key metrics and analyzing early-stage product data when applicable.

What You Bring

• Strong experience in product analytics or a similar data-focused role, with a proven ability to impact product strategy and decision-making through data.
• Expertise in translating complex data into insights that are actionable for cross-functional teams.
• Proficiency with data analytics tools and platforms (e.g., Looker, Amplitude) is a plus but not required. A focus on solving product challenges is more important than specific tool experience.
• Experience in building and maintaining reliable analytics infrastructures.
• Excellent communication skills, with the ability to clearly present data insights to both technical and non-technical stakeholders.
• Experience with 0 to 1 product initiatives is a plus, though not required.
• A high level of accountability, a passion for continuous learning, and the ability to thrive in a fast-paced, dynamic environment.

Qualifications

• Degree in Analytics, Applied Mathematics, Economics, Statistics, or related analytical field of study, or an equivalent combination of training and experience.
• Deep experience in working with exploratory analysis projects related to cohorting, time series analysis, and funnel analysis/optimization is required.
• Expert-level proficiency in influencing product strategy with SQL, A/B testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc., is required.
• Previous or current experience supporting SaaS (Product-Led Growth) companies with uncovering gaps and recalibrating activation metrics (e.g., aha/habit moments) is a huge plus.
• Experience with Product Analytics tools to track end-to-end journeys/funnels (Amplitude, Heap, Mixpanel) and analyzing events within those products is essential.
• Proven ability to thrive in a fast-paced, dynamic startup environment with a high level of adaptability and a strong product sense, ensuring insights align with customer needs and product goals.