Associate Director, Global Data, Platforms and Partnerships GCSO

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

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science Portfolio Management

Job Category:

People Leader

All Job Posting Locations:

Raritan, New Jersey, United States of America

Job Description:

We are searching for the best talent for Associate Director, Global Data, Platforms & Partnerships - GCSO to be in Raritan, NJ.

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 

Purpose:

The Associate Director, Global Data, Platforms & Partnerships is a hands-on, hybrid role of data steward & data feasibility analyst.

The Associate Director will have data stewardship responsibilities that include governance and support for several datasets, to ensure data quality, integrity, security and compliance. He / She will partner with the technology team to maintain and update metadata repositories, ensuring that data definitions, data dictionaries, lineage, and relationships are well documented and accessible to users. He / She will develop deep familiarity with the various real-world datasets such as Optum, IBM Merative MarketScan, Flatiron, etc, that exist within the global data lake.

The Associate Director will partner with data users across the company, to understand data requirements, evaluate real world data sources, and conduct analyses to determine the feasibility of the various data sets and recommend the best data source to answer a key business question or a key research question.

You will be responsible for:

Major responsibilities of this role are data stewardship, data intelligence and data feasibility. This position entails a significant amount of hands-on analytics responsibility.

Key partnership will be with the internal global commercial data science and real-world evidence teams for key commercial and research activities. In addition, there will be close partnership with J&J Technology (JJT) data sciences. This position will report to the Senior Director, Global Data, Platforms & Partnerships.

This includes the following:

Data Feasibility

• Collaboration: Work with data users across the company to understand project goals and technical requirements. Collaborate with stakeholders to gather input and feedback on data needs and potential solutions.

• 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: Conduct feasibility assessments for proposed initiatives. Outline potential challenges, costs, benefits, and timelines associated with the project.

• Risk Assessment: Identify potential risks, 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 & Enablement

• Dataset literacy: Know the data source, nuances of the dataset, what differentiates it, how and where it can be used, including different types and formats (structured vs. unstructured).

• Data Quality Management: Monitor and validate data quality. Identify and address discrepancies or issues in datasets. Ensure data is presented accurately and eff