The job, in the employer's words
About the company
Our client is a healthcare technology company.
The role
Raydar is recruiting for this role on behalf of our client. Serve as the analytical lead for a portfolio of client engagements, shaping modeling work from early data setup through live deployment. Spend much of the time in conversation with business and technical counterparts, explaining methods and converting commercial questions into measurable analytical work.
What you'll do
- Take responsibility for client relationships and the full analytical lifecycle, including data onboarding, study planning, deployed models and continuous refinement.
- Develop predictive models for audience targeting and marketing, including segmentation, propensity scoring and campaign optimization.
- Plan commercially focused studies and justify the approach to senior audiences.
- Run models in production on a public cloud, with automated deployment practices and ongoing performance monitoring.
- Partner with business, analytics and IT counterparts at client organizations to shape practical analytical solutions.
- Pass along recurring client needs and themes to the internal product group.
Requirements
What we're looking for
- Background in the commercial side of large pharmaceutical companies, such as healthcare provider targeting, field teams or sales support; wider biopharma data science experience is also considered, while purely clinical or R&D work is a weaker match.
- Track record of building data and machine learning pipelines, including ETL/ELT and predictive modeling.
- Proven ability to take a model from concept to a working production deployment.
- Experience leading technical delivery for clients across the engagement, from early scoping and solution design through implementation and integration after the sale.
- Strong Python and SQL skills plus working knowledge of a major cloud provider.
- Confident, polished communication with clients, including leading technical workshops and presenting findings to senior stakeholders.
- Self-starter attitude and willingness to take on varied responsibilities in a small, quick-moving team.
Bonus points
- Exposure to large language model applications or AI agents, such as prompt design, guardrails and observability.
- Experience in an early-stage or high-growth startup, in a founding or senior technical capacity.
- Prior predictive modeling work on commercial pharma problems, including specialty or rare disease launches.
Benefits
Compensation and benefits
- Base salary: USD 220,000 to 260,000 per year
- Equity
- Performance bonus
Location and work model
- Remote (US)
- Full-time
Benefits mentioned
- Compensation and benefits
- - Base salary: USD 220,000 to 260,000 per year
- - Equity
- - Performance bonus
- Location and work model
- - Remote (US)
- - Full-time
Requirements mentioned
- What we're looking for
- - Background in the commercial side of large pharmaceutical companies, such as healthcare provider targeting, field teams or sales support; wider biopharma data science experience is also considered, while purely clinical or R&D work is a weaker match.
- - Track record of building data and machine learning pipelines, including ETL/ELT and predictive modeling.
- - Proven ability to take a model from concept to a working production deployment.
- - Experience leading technical delivery for clients across the engagement, from early scoping and solution design through implementation and integration after the sale.
- - Strong Python and SQL skills plus working knowledge of a major cloud provider.
- - Confident, polished communication with clients, including leading technical workshops and presenting findings to senior stakeholders.
- - Self-starter attitude and willingness to take on varied responsibilities in a small, quick-moving team.
- Bonus points
- - Exposure to large language model applications or AI agents, such as prompt design, guardrails and observability.
- - Experience in an early-stage or high-growth startup, in a founding or senior technical capacity.
- - Prior predictive modeling work on commercial pharma problems, including specialty or rare disease launches.
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