Data Scientist leading commercial data science function at Novellia transforming healthcare data insights. Presenting metrics and trends to biopharma clients and building analytics solutions.
Responsibilities
Build and lead our commercial data science function from the ground up
Serve as the primary analytics point of contact for client inquiries, responding to questions about our data, methodologies, and analytical capabilities
Present patient recruitment metrics, growth trends, and study insights in weekly meetings with biopharma partners
Design and build internal analytics solutions that improve how we serve clients—dashboards, reporting frameworks, and data quality monitoring systems
Collaborate with the data and engineering teams to develop scalable data pipelines that power both client deliverables and internal operations
Drive data quality initiatives to ensure accuracy and reliability across all client-facing analytics
Define best practices for research-grade analytics delivery in the real-world evidence space
Contribute to business development efforts by articulating our analytical capabilities to prospective clients
Identify patterns across client engagements that inform product development and company strategy
Requirements
5-8 years of experience in data science or analytics, with at least 3 years in a client-facing or consulting capacity
Deep proficiency with data analytics tools: SQL, Python, Snowflake, BigQuery, Redshift
Strong command of data visualization tools (e.g. Metabase, Looker) and ability to design and implement dashboards for non-technical audiences
Experience building analytics solutions from scratch—data models, pipelines, reporting frameworks, and dashboards
Proven track record of translating ambiguous business questions into concrete analytical approaches and deliverables
Exceptional ability to present complex analytical insights to diverse audiences, from software engineers to C-suite biopharma executives
Demonstrated success building trusted relationships with external stakeholders through consistent, high-quality delivery
Comfortable managing competing priorities from multiple clients while maintaining quality and responsiveness
Strong individual contributor who can design and build solutions independently
Familiarity with advanced analytics techniques including statistical modeling, machine learning fundamentals, and predictive analytics
Ability to evaluate data quality, identify issues, and implement monitoring systems
Experience working with healthcare data (EHR, claims, registry data) is a strong plus but not required.
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