Senior Data Scientist

At Mindera, we believe that software is built by people, for people, with high-performance systems that impact users worldwide. We are looking for a SeniorData Scientist to join an agile, collaborative team where your voice matters as much as your code.

The Data Scientist is a high-level individual contributor who leads complex data science initiatives that impact the Core Tech roadmap. This role focuses on translating complex marketing and product challenges into data-driven recommendations. Working with significant independence, the Senior Data Scientist develops predictive models and performance reporting frameworks that enable stakeholders across the organization to make informed investment decisions.

We value empathy, self-organization, and a positive attitude. If you are approachable, communicate clearly, and believe that team fit is just as important as technical prowess, you'll feel right at home here.

At Mindera we encourage the use of AI to assist with coding and related tasks. We find a persons skill in engineering and software craft, has a big impact long term successful delivery, with or without AI. Our goal in the interview process is to understand the candidates knowledge and skill with engineering.

If you need to, or plan to use AI, please be transparent with us when you're using it, to avoid issues and misunderstandings that can either: impact your chance of securing the role or impact your success at Mindera.

National and international expected traveling time varies according to project/client and organizational needs: 0%-15% estimated.

💪 How You'll Contribute

• Problem Framing: Partner directly with Marketing and Product leadership to turn vague business problems into clear metrics and actionable hypotheses.
• Statistical Modeling & Causal Analysis: Build, iterate, and monitor statistical models. Distinguish genuine causal impact from correlation to optimize marketing spend and product growth.
• Experimentation & Prototyping: Design holdout tests and quasi-experiments (or A/B tests) where clean randomization isn't possible. Move rapidly from hypothesis to verified proof-of-concept.
• Data Storytelling: Translate complex algorithmic behavior into simple, visual narratives for US/UK stakeholders.