Senior Data Scientist

Role overview

Join Bluesight as a Senior Data Scientist in a fully remote role. You’ll partner with internal and external stakeholders to deliver end-to-end data science and analytics impact across the organization.

Key missions

• Collaborate cross-functionally to identify opportunities and deliver value across the R&D life cycle.
• Develop and productionize machine learning models for healthcare products.
• Define and track KPIs to measure and improve model performance.
• Communicate insights to both technical and non-technical stakeholders and inform product roadmaps.
• Raise team skill levels via code reviews and feedback on experimental design.

Responsibilities

• Productionize ML solutions and integrate them into services/APIs.
• Work with product teams and stakeholders to translate analysis into roadmap priorities.
• Present technical findings clearly to varied audiences.

Requirements

• Ability to develop and productionize Python code serving API endpoints (e.g., Flask, FastAPI).
• Master-level SQL.
• Degree (or equivalent years of experience) in data science, statistics, computer science, or a related quantitative field.
• Strong statistical modeling fundamentals (including distributions and transformations).
• Ability to build and evaluate supervised and unsupervised ML models (e.g., tree-based models, clustering) in applied contexts.
• Hands-on experience with AWS services including SageMaker, Athena, RDS, Glue, ECR, IAM, CodeBuild.
• Strong Git workflows and version control best practices.
• Excellent communication skills with the ability to advocate solutions to engineering and business stakeholders.
• Track record of presenting analysis for non-technical audiences.
• Experience working on a data team of similar size (<5).
• Master’s degree or PhD in math/statistics-centric field.

Nice to have / Additional experience

• Experience with genAI tools to accelerate experimentation.
• Experience with protected healthcare data (e.g., ADM, EHR) and pharmaceutical supply chain logistics.
• Experience with Infrastructure as Code using Terraform.
• MLOps experience: deployment using MLflow, Docker containerization, CI/CD, and monitoring.