Associate Director Solutions Partner (Scientific Data Product Owner)

Location: Tarrytown, New York, United States; 4 days onsite per week required

Salary: $157,200–$256,600 annually

Company

hirify.global operates in the biopharmaceutical and life sciences sector, with work focused on scientific research and data-driven product development.

What you will do

• Define the strategy, vision, roadmap, and backlog for connected scientific data products in the enterprise data lake.
• Partner with data engineering teams on ingestion, transformation, integration, and ETL/ELT pipelines from ELN, LIMS, instrument, analytical, and registration systems.
• Design and govern data models connecting compounds, biologics, samples, assays, experiments, results, instruments, and study metadata.
• Translate scientific, technology, and analytics needs into product requirements, acceptance criteria, and delivery plans.
• Deliver documented, analytics-ready datasets for data science, modelling, reporting, and AI/ML use cases.
• Establish data quality, governance, metadata, lineage, and FAIR principles while improving AI-driven scientific data discovery.

Requirements

• Advanced degree in a biology discipline required; a PhD in molecular biology, biochemistry, genetics, or immunology is preferred.
• 10+ years of progressive experience managing scientific laboratory data, ideally in biopharmaceutical or life sciences environments.
• Strong background in chemistry, biology, molecular biology, biochemistry, immunology, pharmacology, or a related discipline.
• Hands-on experience with data modeling, connecting multiple source systems, product ownership, roadmap definition, backlog prioritization, and stakeholder management.
• Strong SQL skills and proficiency in a primary Databricks language such as SQL or Python/PySpark.
• Working knowledge of data pipelines, ETL/ELT, data transformation, ELN, LIMS, and analytical data platforms.

Nice to have

• Hands-on experience with Databricks or a comparable lakehouse platform.
• Experience with AI-driven data discovery, knowledge graphs, ontologies, controlled vocabularies, or semantic data models.
• Experience with data governance, FAIR principles, metadata management, data catalogs, and data lineage tools.
• Experience working with data scientists and analytics teams on AI/ML-ready datasets.
• Awareness of regulatory and compliance requirements for pharmaceutical R&D data.

Culture & Benefits

• Collaborative work across scientific, data engineering, Digital & Technology, product, and analytics teams.
• Inclusive workplace with reasonable accommodations available during recruitment where required.
• Competitive total rewards package that may include bonuses, equity, retirement benefits, health and wellness programs, insurance, paid time off, and family support benefits.
• Many roles are designed to be performed onsite, with expectations discussed during the recruitment process.