INTL - Research Data Owner

Job Description

The Research Data Owner (RDO) provides enterprise-level leadership, governance, and strategic direction for high-value research datasets used across the Data, Automation & Predictive Sciences (DAPS) organization. This role ensures that shared, cross-domain scientific data is trustworthy, compliant, well-curated, and optimized for advanced analytics, automation, and predictive modeling. The RDO acts as the central authority for lifecycle management, risk acceptance, and consumption of foundational research datasets that power discovery and translational science.

This is a highly collaborative role that interfaces with scientific, technical, and governance stakeholders to drive data quality, interoperability, and responsible reuse across the biopharmaceutical R&D ecosystem.

Key Responsibilities

Strategic Data Ownership & Stewardship

Provide enterprise-level ownership for shared research datasets, curated internal lists, and foundational scientific data assets used across DAPS and R&D.

Serve as the central decision-maker for dataset lifecycle strategy, risk acceptance, and cross-functional consumption.

Oversee datasets sourced from public repositories (e.g., GEO, NCBI, CellXGene, OpenTargets) and internal reference data (e.g., genome builds, annotation files, human cell/protein atlases).

Governance, Compliance & Regulatory Leadership

Establish and enforce governance standards, frameworks, and policies for research data.

Ensure compliance with global and regional data protection, licensing, consent, and research-use regulations.

Partner with Legal, Privacy, IP, and Risk & Compliance teams to ensure responsible and compliant data use.

Maintain oversight of FAIR and ALCOA+++ principles across all shared datasets.

Cross-Functional Collaboration & Scientific Partnership

Partner with federated Business Data Owners (BDOs) to harmonize governance approaches across scientific domains.

Collaborate closely with Business Data Stewards (BDS), Data Architects, Knowledge Engineers, and Research Tech teams.

Translate data strategy into operational execution, including schema definitions, ontologies, metadata standards, and documentation to support reproducibility and interoperability.

Data Lifecycle Oversight

Oversee the end-to-end lifecycle of shared datasets, including acquisition, ingestion, curation, versioning, reuse, retention, and retirement.

Define and monitor lifecycle KPIs and quality metrics.

Identify and mitigate risks related to data quality, privacy, security, and intellectual property adherence.

Continuous Improvement & Innovation

Lead initiatives to enhance governance frameworks, data standards, and operational processes.

Conduct exploratory investigations to identify trends, anomalies, and opportunities for improved data utility.

Champion adoption of emerging industry standards, technologies, and best practices in research data management.

Stakeholder Communication & Reporting

Communicate strategic decisions, risks, and value outcomes to scientific and technical stakeholders.

Ensure alignment between enterprise data strategy and operational execution by BDS and federated BDOs.

Advocate for improvements in data management, curation, metadata practices, and data literacy across the organization.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Bachelor's or Master's degree in Bioinformatics, Computational Biology, Data Science, Life Sciences, or related field.

Experience in research data governance, data stewardship, or scientific data management within biopharma, biotech, or academic research.

Strong understanding of FAIR data principles, data lifecycle management, and regulatory considerations for research data.

Familiarity with public scientific data repositories and foundational biological datasets.

Demonstrated ability to work across scientific, technical, and governance functions.

Excellent communication skills with the ability to translate complex data concepts into actionable guidance. Experience working in a Data, Automation & Predictive Sciences (or similar) organization.

Knowledge of ontologies, controlled vocabularies, and semantic data modeling.

Understanding of cloud-based data platforms, data engineering workflows, and modern analytics ecosystems.

Experience supporting AI/ML, automation, or predictive modeling use cases.