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Job Summary:
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications. The Director of Data Solutions is responsible for leading the technical delivery of data platforms and AI/ML solutions, while establishing an organization-wide modeling and simulation practice to ensure high-quality outcomes.
Responsibilities:
• 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.
• 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.
• 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.
• 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.
• 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 ML+simulation opportunities.
• 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.
• 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.
Qualifications:
Required:
• 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:
• 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.
Company:
At Axle, we are driven by the mission to accelerate discovery and enhance organizational outcomes by revolutionizing operations with our innovative solutions. Founded in 2002, the company is headquartered in Rockville, USA, with a team of 501-1000 employees. The company is currently Late Stage.