Data Scientist supporting management consultants conduct data analysis and providing strategic decision - making insights. Involves data processing, model development, and collaborative problem - solving with clients.
About the role
- Manager, Data Science in Oncology supporting data engineering and R&D projects at Johnson & Johnson. Leading technical contributions and collaborating with diverse teams in healthcare data.
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.
- 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.
- Experience with healthcare data standards (e.g. CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM).
- Familiarity with machine learning operations (MLOps) and model deployment.
Benefits
- medical
- dental
- vision
- life insurance
- short- and long-term disability
- business accident insurance
- group legal insurance
- consolidated retirement plan (pension)
- savings plan (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
- personal and family time - up to 40 hours per calendar year
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