Director of Data Solutions

(ID: 2026-1572)

Axle is a bioscience and information technology company that offers advancements in translational research biomedical informatics and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science software engineering and program management we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

• 100% Medical Dental & Vision Coverage for Employees
• Paid Time Off and Paid Holidays
• 401K match up to 5%
• Educational Benefits for Career Growth
• Employee Referral Bonus
• Flexible Spending Accounts:
  • Healthcare (FSA)
  • Parking Reimbursement Account (PRK)
  • Dependent Care Assistant Program (DCAP)
  • Transportation Reimbursement Account (TRN)

The Director of Data Solutions is the senior technical delivery leader for data platforms AI/ML solutions (including GenAI) and advanced modeling/simulation capabilities. This leader owns the how and when of building reusable enterprise-grade capabilities that turn complex multimodal data into trusted products and measurable outcomes.

In practice this role:

• Sets technical strategy and reference architecture across modern data stacks and cloud environments.
• Leads cross-functional teams (data engineering ML engineering applied science software engineering) to ship and operate production systems.
• Establishes an organization-wide modeling and simulation practice that ensures reproducibility compute strategy and strong quality standards.

KEY RESPONSIBILITIES

Technical strategy & architecture

• Define reference architectures and technical standards for data/AI platforms (security scalability reliability cost governance developer experience).

• Own platform modernization plans and technical debt reduction sequencing.

• Make build/buy/partner decisions and establish patterns that can be reused across programs.

Interoperability harmonization & data quality

• Lead delivery of repeatable ingestion and transformation pipelines with testing validation and change control.

• Own harmonization capabilities (terminology translation unit normalization episode building) as production services with documentation and quality dashboards.

• Partner with governance and stakeholders to define minimum acceptable quality and publish transparent quality measures.

AI/ML and GenAI solution delivery

• Lead delivery of production AI/ML solutions (NLP CV predictive models representation learning) and deploy them with evaluation and monitoring.

• Own GenAI patterns and platforms (RAG agentic workflows human-in-the-loop review traceability privacy safeguards) as reusable services.

• Establish model lifecycle governance: approvals audits (as needed) drift monitoring incident response and continuous improvement.

Realworld evidence enablement engines

• Build reusable engines for RWE execution: cohorting/phenotyping pipelines reproducible protocol templates causal inference/target trial tooling patterns and integration templates for multiple data sources.

• Staff and support analysis pods for time-sensitive high-stakes deliverables with rigorous QC and reproducibility practices.

Simulations & modeling practice leadership

• Define the modeling/simulation practice charter: scope service model standards compute strategy (HPC/cloud) and hiring/partnering plan.

• Lead simulation/modeling teams directly or via domain SMEs; ensure reproducible workflows and high quality bars.

• Identify and prioritize high-value hybrid MLsimulation opportunities.

Privacy security & operational excellence

• Partner with security/privacy to implement strong access controls auditability and (where needed) privacy-preserving approaches.

• Establish operational excellence: release management observability on-call/incident processes (as appropriate) and runbooks.

People leadership & culture

• Hire grow and retain a high-performing organization; create clear roles career paths and performance expectations.

• Build a culture of research-grade rigor production-grade discipline emphasizing accountability documentation and sustainability.

REQUIRED QUALIFICATIONS

• 6 years in data science ML engineering data platform engineering applied research engineering or closely related fields

• 3 years leading multi-disciplinary teams.

• Demonstrated success delivering production data/AI platforms (not only analyses) including architecture delivery planning and operational ownership.

• Strong familiarity with modern data stacks and cloud delivery (distributed compute ETL/ELT data quality tooling MLOps/LLMOps concepts).

• Ability to translate ambiguous stakeholder needs into shipped products and measurable outcomes.

• Strong people leadership: recruiting coaching performance management org design.

• Comfort operating in regulated and high-governance environments (privacy compliance access control).

PREFERRED QUALIFICATIONS

• Healthcare data platform experience especially interoperability/harmonization at scale (OMOP/FHIR/PCORNet/CDISC) and clinical terminology systems.

• Experience shipping GenAI solutions with governance (PII handling traceability human review evaluation monitoring).

• Experience with privacy-preserving ML patterns (federated learning/inference) and/or sensitive data platforms.

• Experience leading simulation/modeling initiatives (scientific computing HPC workflows domain simulations) and partnering effectively with scientific SMEs.

• Track record of publications open-source leadership or scientific impact.

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills responsibilities duties and/or assignments required. Individuals may be required to perform duties outside of their position job description or responsibilities as needed.

The diversity of Axles employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age race gender religion national origin disability marital status covered veteran status sexual orientation status with respect to public assistance and other characteristics protected under state federal or local law and to deter those who aid abet or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidates experience qualifications skills and location.

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Salary Range

$170000 - $210000 USD