Associate Director, Global Data Science (GCSO)

Johnson & Johnson is currently seeking an Associate Director, Global Data Science to join our Global Commercial Strategy & Operations team located in Raritan, NJ.

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 https://www.jnj.com/.

The Associate Director, Global Data Science is a hands-on, hybrid role of data feasibility analyst and data steward.

The incumbent will conduct feasibility assessments for proposed initiatives, outlining potential challenges, costs, benefits, and timelines associated with the project.

He/She will also operationalize and drive optimal usage of real-world data with stewardship responsibilities for a few datasets, primarily HealthVerity data, to ensure the quality, integrity, and usability of data.

Key partnerships will be with the internal global commercial data science and real-world evidence teams for key commercial and research activities and with J&J Technology (JJT) data sciences.

This individual will report to the Senior Director, Global Data, Platforms & Partnerships.
Responsibilities:
Data Feasibility


* Data Assessment: Evaluate existing data sources to determine their relevance, quality, and availability for specific projects.

Analyze data requirements from stakeholders and assess how well current datasets meet those needs.


* Feasibility Assessment: Understand the data requirements, evaluate real world data sources, and conduct analyses to determine the feasibility of the various data sets and select the best data source to answer a key business question or a key research question.


* Collaboration: Work with the commercial data scientists to understand project goals and technical requirements.

Work with stakeholders to gather input and feedback on their data needs and potential solutions.


* Risk Assessment: Identify potential risks and evaluate compliance considerations that may impact data utilization.


* Recommendations: Provide actionable recommendations based on feasibility assessments, including alternative data sources or methodologies.

Present findings in clear and concise formats (e.g., presentations, reports).


* Documentation: Document findings, methodologies, and processes.

Data Stewardship


* Dataset literacy: Develop deep familiarity with the various real-world data sources that exist within the global data lake, such as HealthVerity, Optum, IBM Merative MarketScan.

Understand and communicate the nuances of the dataset, what differentiates it, how and where it can be used, including different types and formats...