Work directly with stakeholders (engineers, program managers, subject matter experts) to scope problems, formulate the right analytical questions, and translate business challenges into rigorous data science approaches.
Apply deep analytical thinking to decompose complex problems—critically evaluate data quality and relevance, challenge assumptions, and design methods that address the business need.
Develop statistical models, machine learning solutions, and analytical frameworks that deliver actionable insights and drive operational decisions.
Build user‑friendly, production‑grade ML/AI applications (e.g., Streamlit, Dash) and analytical artifacts that provide data insights to teams across the enterprise and enable better decision making.
Write production-quality Python code and develop analytical pipelines using cloud-based platforms (AWS, Databricks) to support scalable and reproducible data science workflows.
Deliver insights through multiple channels—executive recommendations, analytical reports, interactive dashboards, and direct consultation with business leaders.
Take ownership of the technical quality and business impact of your work—make thoughtful methodological decisions, validate approaches rigorously, and stand behind your recommendations.
Stay current on analytical methods, statistical techniques, and domain-specific best practices to continuously improve the quality and impact of your work.

Bachelor’s degree with 5+ years of relevant professional experience in data science or data analysis – OR – Master’s degree with 3+ years of relevant professional experience in data science or data analysis.
Proficiency with Python, SQL, and Git.
Deep understanding of statistical methods, machine learning algorithms, and when to apply different analytical techniques.
Experience developing and deploying machine learning models in production environments.
Proven ability to translate complex business problems into rigorous analytical frameworks.
Demonstrated problem‑solving and critical‑thinking skills with an ability to handle complex analytical challenges.
Excellent communication skills and ability to deliver compelling, actionable recommendations to non‑technical stakeholders.
Strong track record of ownership and accountability for technical decisions and project outcomes.

Data Scientist – Insights & Intelligence

Key skills