Senior Data Scientist

Harnham; North Carolina; Remote; USD 171,000 - 209,000; Full time

Job summary

Harnham partners with a fast-growing healthcare technology company hiring multiple Senior Data Scientists to expand their Data Science function. You will own ML problems end-to-end, from feasibility to production, with a focus on patient matching, engagement, forecasting and decision support.

Ideal candidates have 5+ years of hands-on DS experience, strong Python/SQL, and a track record of deploying models to production. Remote US-based work with EST alignment is offered.

Qualifications

• 5+ years of hands-on Data Science experience
• Strong Python and SQL
• Strong foundation in predictive modeling and statistics
• Experience building models that have been deployed into production
• Experience with experimentation and model evaluation
• Ability to independently tackle ambiguous, open-ended problems
• Strong communication skills across technical and non-technical teams

Responsibilities

• Build and deploy predictive models that improve patient matching and engagement
• Develop recommendation systems and forecasting models
• Design experiments and apply statistical methods to understand what actually drives outcomes
• Turn ambiguous healthcare and product problems into well-defined Data Science solutions
• Own models from initial development through deployment, monitoring, and iteration
• Partner directly with Product and Engineering to identify where ML can create the most value
• Translate model performance and analytical findings into decisions that non-technical stakeholders can act on

Skills

5+ yrs DS

Python

SQL

Predictive modeling

Statistics

Production deployment

Experimentation

Communication

Tools

Databricks

Snowflake

Cloud ML tooling

Job description

Most Data Scientists want their models to make it into production.

This is a chance to build ones that could help a patient access the right clinical trial.

Harnham is partnered with a fast-growing healthcare technology company hiring multiple Senior Data Scientists as they significantly expand their Data Science function.

The team is building machine learning products around patient matching, engagement, forecasting, and decision-making. You'll own problems end-to-end, from figuring out whether ML is the right solution through experimentation, modeling, deployment, and measuring performance in production.

This is not a research-only position. The expectation is that what you build gets used.

What You'll Do

• Build and deploy predictive models that improve patient matching and engagement
• Develop recommendation systems and forecasting models
• Design experiments and apply statistical methods to understand what actually drives outcomes
• Turn ambiguous healthcare and product problems into well-defined Data Science solutions
• Own models from initial development through deployment, monitoring, and iteration
• Partner directly with Product and Engineering to identify where ML can create the most value
• Translate model performance and analytical findings into decisions that non-technical stakeholders can act on

What We're Looking For

• 5+ years of hands-on Data Science experience
• Strong Python and SQL
• Strong foundation in predictive modeling and statistics
• Experience building models that have been deployed into production
• Experience with experimentation and model evaluation
• Ability to independently tackle ambiguous, open-ended problems
• Strong communication skills across technical and non-technical teams

Especially Relevant Experience

Healthcare, life sciences, biotech, pharma, or health insurance experience will be highly valuable.

Experience with causal inference, recommendation systems, forecasting, Bayesian methods, experimentation, Databricks, Snowflake, or modern cloud ML tooling is also a plus.

Why Consider It?

• Up to $190,000 base salary
• Fully remote within the US (EST)
• Multiple Senior Data Scientist hires
• Build ML products with a direct connection to patient outcomes
• Genuine ownership from problem definition through production
• Work closely with Product and Engineering rather than operating as a separate research function
• Join while the company is making a significant investment in Data Science and ML
• Opportunity to influence how the team approaches modeling, experimentation, and production ML as it scales