Data Scientist in Digital Transformation team at Lavazza implementing machine learning models and managing model lifecycle within Agile squads. Focusing on solving real business problems.
About the role
- 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.
Benefits
- Health insurance
- Flexible work arrangements
- Professional development opportunities
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