Data Science Product Lead

We are a fast growing and well funded startup in the SaaS B2B space. We are an experienced team and serial founders with previous successes. We manage to sell founder-led, and the customers are happy. 

The core of our product is a Bayesian marketing mix model. We already have a very strong modeling team, and also a deep understanding of the actual business problem. We have the capabilities to make what we want to make, however we both need more manpower, brains and some help with prioritizing and structuring the model development. 

About the Role

As a Data Science Product Lead, you will operate at the intersection of business, modeling, and platform, with a primary focus on prioritizing and shaping the long-term direction of the product offering.

you will work closely with the modeling team to translate real-world business constraints, customer needs, and domain knowledge into clear modeling requirements. While you will not be responsible for day-to-day model development, you are expected to be technically fluent—able to engage in deep discussions about implementation details of the models, challenge assumptions, and understand the business impact of modeling decisions.

At the same time, we are looking for a high-aptitude individual who is comfortable contributing hands-on when and where it makes sense. This includes directly implementing small features, prototypes, or improvements in the codebase.

Key Responsibilities

• Own and drive prioritization of model-related development

• Help maintain a clear and shared vision of the target state of the models and platform

• Translate customer needs, business rules, and constraints into actionable modeling requirements

• Act as a sparring partner across modeling, customer success, and platform

• Talk to customers, monitor competitors, and build deep expertise in marketing mix modeling

• Prototype features and ideas

Skills & Experience

• Master of Science (PhD is a plus)

• Strong communication skills across technical and non-technical stakeholders

• Experience working with and building data science solutions

• Comfortable working in an early-stage environment/company

• Experience with marketing mix modeling, marketing analytics

• Worked extensively with Python in a business environment

• Familiarity with Bayesian modeling and/or causal inference

• Background from startups or high-growth SaaS companies