Are you passionate about turning data into actionable insights? Do you thrive in cross-functional environments where your work directly influences product, strategy, and customer experience?

We’re looking for a Data Scientist to join our dynamic team and help shape the future of data-driven decision-making. In this role, you’ll collaborate across departments to deliver high-impact analytics and machine learning solutions.

• Own core analytics and reporting in Power BI — define trusted datasets, build executive/product dashboards, and ensure performance and data quality.
• Define clear company metrics — establish KPI definitions and a lightweight data dictionary, plus simple guardrails for data access and quality.
• Partner with engineering on high-level data architecture and pipelines — prioritize what matters now, document what comes next.
• Design practical measurement plans — including experiments, A/B tests, and pre/post analyses to evaluate product changes and business impact.
• Collect, clean, and analyse large datasets, both structured and unstructured.
• Develop, test, and implement statistical models and machine learning algorithms to drive informed decision-making.
• Translate business problems into data science solutions and present findings in a clear, actionable way.
• Build data-driven dashboards, reports, and visualizations to communicate insights.
• Stay up to date with emerging data science methods, tools, and best practices.

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related field.
• 2+ years of experience as a Data Scientist.
• Strong programming skills in Python, R, or Scala.
• Proficiency with SQL and data manipulation.
• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Skilled in data visualization tools (Power BI, Tableau, or equivalent).
• Solid understanding of statistics, probability, and experimental design.
• Strong communication skills to explain technical concepts to non-technical stakeholders.
• Comfort working with sensitive/health-related data and privacy considerations.

• PhD in a quantitative field.
• Experience with big data technologies (e.g., Spark, Hadoop).
• Familiarity with cloud platforms (Azure, AWS, etc.).
• Previous experience in healthcare or biotechnology.
• Experience building analytics from 0→1 in a startup or fast-moving environment.
• Exposure to product experimentation and causal inference.