Senior Data Scientist applying advanced analytics and data science techniques for P&C insurance solutions. Collaborating with stakeholders to improve pricing accuracy and risk management.
About the role
- Manager in Data Science for Oncology, supporting data workflows and engineering requirements in R&D. Collaborate with technical teams to deliver AI-ready data applications for innovative medicine.
Responsibilities
- Serve as both a people leader and a hands-on contributor for designing, developing and maintaining data pipelines for acquiring, managing and storing Oncology R&D data from diverse sources (e.g. biomarker labs, real-world data sources, pre-clinical applications)
- Work closely with Data Science and Oncology R&D partners to understand, document and prioritize business requirements. Translate these business needs in to high quality data products.
- Work closely with other technical leaders, such as Ontology and Knowledge graph Engineers to design and deliver future-proof, AI-ready data systems aligned with Oncology R&D business needs.
- Develop Oncology R&D-specific data repositories by implementing standard enterprise-level data models and create new data models as needed.
- Leverage cloud-based technology platform to accomplish goals, such as building and maintaining data repositories using AWS S3.
- Create and optimize data flows for structured and unstructured data using technologies such as Python, R, SQL, AWS services and other relevant tools.
- Implement quality and performance standards and measure KPIs to determine accuracy and consistency
- Leverage and implement data versioning and lineage tracking to support data traceability, compliance, maintaining documentation for data architectures and workflows.
- In adherence to internal standards, implement software development best practices such as Code Versioning, DevOps.
Requirements
- Advanced degree (Master’s or equivalent) in Computer Science, Engineering, Life Sciences, or other relevant field is strongly preferred. (Bachelor’s Degree with experience equivalency may be considered.)
- 5+ years of experience in data engineering, including data modeling and database design, preferably in the healthcare industry
- 2+ years experience managing a technical team aimed at delivering data systems, preferably in the healthcare industry.
- Proficiency in data engineering tools such as Python, R and SQL for data processing as well as cloud architecture (e.g. AWS services, Redshift, FSx, Glue, Lambda).
- Experience with unstructured database technologies (e.g. NoSQL) as well as other database types (e.g. Graph).
- Strong skills in analysis, problem-solving, organizational change, project delivery, and managing external vendors.
- Proven record leading improvement initiatives with multi-disciplinary and remote partners.
- Demonstrated stakeholder management capabilities- including requirements gathering, business analysis and planning.
- Must have the capacity to translate discussions into user requirements and project plans.
- Ability to manage a numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
- Willingness to conduct periodic travel (<15% of time) to conferences and internal meetings.
Benefits
- medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance
- 401(k)
- Vacation – up to 120 hours per calendar year
- Sick time - up to 40 hours per calendar year
- Holiday pay, including Floating Holidays – up to 13 days per calendar year
- Work, Personal and Family Time - up to 40 hours per calendar year
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