Principal Data Scientist, R&D Oncology

Johnson & Johnson Innovative MedicineSan Diego, CA
1dOnsite

About The Position

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com. As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: Scientific/Technology All Job Posting Locations: Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, San Diego, California, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America Job Description: Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine Johnson & Johnson Innovative Medicine is recruiting for a Principal Data Scientist, R&D Oncology to join our Data Science and Digital Health team (DSDH). This position will be located at one of our offices in either Spring House PA (preferred), Cambridge MA, or San Diego CA (La Jolla area). Consideration may be given for our Titusville and Raritan, NJ locations. The Principal Data Scientist, R&D Oncology will support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements. This role will focus on applications in Oncology R&D and support data projects from across the business including Clinical, Pre-Clinical, RWD and ‘omics platforms. This role will be a leading technical contributor and creative problem solver with developing AI-ready data and other routinely used data applications for Oncology R&D.

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.)
  • 3+ years of experience in data engineering, including data modeling and database design, 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.

Nice To Haves

  • Experience with healthcare data standards (e.g. CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM).
  • Exposure to high dimensional data technologies and handling, including imaging.
  • Familiarity with machine learning operations (MLOps) and model deployment.

Responsibilities

  • Design, develop and maintain 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.

Benefits

  • Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance.
  • Employees may be eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
  • Employees are eligible for the following time off benefits: 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 of Work, Personal and Family Time - up to 40 hours per calendar year
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