Director, Data Science

Harnham; United States; Remote; USD 265,000 - 300,000; Full time

Job summary

Harnham partners with a major not-for-profit health system in the United States to appoint a Director, Data Science. This leadership role guides an AI/ML team translating complex data into measurable outcomes across customer, clinical, operational, and business domains, collaborating across data, engineering, product, digital, clinical, and operational teams.

The mandate includes defining an enterprise data science roadmap and applying ML to the customer journey, including unstructured data from

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, Operations Research, Public Health, Biomedical Informatics, or related field.
• At least 12 years of experience across data science, ML, analytics, statistics, optimization, or decision science.
• At least 5 years of leadership experience managing data science/analytics teams.
• Proven ability to translate ambiguous problems into production data science solutions with measurable outcomes.
• Strong foundation in ML, predictive analytics, statistical modeling, experimentation, causal inference, optimization, and evaluation.
• Experience operationalizing data science in partnership with engineering, product, and business teams.
• Experience with Python, R, SQL, ML libraries, notebooks, and cloud-based analytics.
• Understanding of deployment, monitoring, interpretability, bias, drift, and lifecycle management.
• Ability to communicate complex analytics to senior stakeholders.
• Experience in privacy, security, compliance, and reliability considerations.

Responsibilities

• Define and execute the enterprise data science roadmap across customer, clinical, operational, and business priorities.
• Identify opportunities where ML, analytics, optimization, and AI deliver measurable value.
• Lead development of predictive, prescriptive, and optimization models across priority domains.
• Oversee forecasting, segmentation, personalization, recommendation systems, propensity modeling, and decision support.
• Transform unstructured customer data into actionable insights and improved experiences.
• Establish standards for model development, experimentation, validation, deployment readiness, monitoring, and lifecycle management.
• Define frameworks for evaluating model performance across value, quality, reliability, fairness, and outcomes.
• Lead experimentation and measurement strategies including A/B testing and causal inference.
• Partner with Data Engineering, AI Engineering, Product, Digital, Clinical, and Operations to productionize models.
• Collaborate with ontology and knowledge teams to incorporate semantic context and enterprise definitions.
• Advise senior leaders on data science strategy, tradeoffs, risk, and measurable outcomes.
• Lead and develop a high-performing team of data scientists.

Skills

Leadership experience

Data science expertise

Communication to senior stakeholders

Python/R/SQL

Cloud analytics environments

ML / predictive analytics

Model deployment & monitoring

Privacy & security awareness

Problem translation to production

Education

Bachelor’s degree or higher in relevant field

Master’s degree or PhD in relevant discipline

Tools

Python

R

SQL

ML libraries

Notebooks

Cloud environments

Job description

Harnham is partnering with one of the largest not-for-profit health systems in the United States to appoint a Director, Data Science. Headquartered in Dallas, the organization operates an integrated network of more than 55 hospitals and 1,300 care sites across Texas, serving more than three million people and supporting approximately 13.5 million patient encounters annually.

The organization is investing significantly in artificial intelligence, advanced analytics, and digital capabilities as part of its continued transformation into a more connected and customer-focused health system. A major priority is improving the experience individuals have outside of direct inpatient care, including how they access information, navigate services, communicate with the organization, and make healthcare decisions.

The Director, Data Science will lead an established AI and machine learning team responsible for translating complex customer, clinical, operational, and business data into measurable outcomes. Working across data, engineering, product, digital, clinical, and operational teams, this leader will shape how data science capabilities are developed, evaluated, and applied across the organization.

The Mandate

The Director, Data Science will define and execute an enterprise data science roadmap aligned with the organization’s customer, clinical, operational, and business priorities. An immediate focus will be applying machine learning and advanced analytics to the customer journey, including unstructured information from surveys, call center interactions, and other customer touchpoints.

The successful candidate will lead the development of semantic data products, personalization and recommendation capabilities, forecasting systems, experimentation frameworks, and decision support solutions. The role will also establish enterprise standards for model development, validation, deployment readiness, performance monitoring, and lifecycle management, ensuring data science solutions are scalable, reliable, and connected to measurable organizational value.

Responsibilities

• Define and execute the enterprise data science roadmap in alignment with customer, clinical, operational, and business priorities.
• Identify and prioritize opportunities where machine learning, advanced analytics, optimization, and AI can deliver measurable value.
• Lead the development of predictive, prescriptive, and optimization models across priority business domains.
• Oversee capabilities related to forecasting, segmentation, personalization, recommendation systems, propensity modeling, and decision support.
• Transform unstructured customer data, including survey responses and call center interactions, into actionable insights and improved customer experiences.
• Establish standards for model development, experimentation, validation, documentation, deployment readiness, monitoring, and lifecycle management.
• Define frameworks for evaluating model performance across business value, statistical quality, reliability, fairness, and customer or clinical outcomes.
• Lead experimentation and measurement strategies, including test design, causal inference, A/B testing, and impact evaluation.
• Partner with Data Engineering, AI Engineering, Product, Digital, Clinical, and Operational teams to integrate models and analytical services into production workflows.
• Collaborate with ontology and knowledge product teams to incorporate semantic context, enterprise definitions, and knowledge models into data science solutions.
• Advise senior leaders on data science strategy, technical tradeoffs, investment priorities, risk, and measurable outcomes.
• Lead, coach, and develop a high performing team of data scientists and analytical practitioners.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, Operations Research, Public Health, Biomedical Informatics, or a related discipline.
• At least 12 years of experience across data science, machine learning, advanced analytics, applied statistics, optimization, or decision science.
• At least five years of leadership experience directly managing data science, analytics, or machine learning teams.
• Demonstrated success translating ambiguous business or customer problems into production data science solutions with measurable outcomes.
• Strong foundation in machine learning, predictive analytics, statistical modeling, experimentation, causal inference, optimization, and model evaluation.
• Experience operationalizing data science capabilities in partnership with engineering, product, and business teams.
• Experience with Python, R, SQL, machine learning libraries, notebooks, and cloud based analytical environments.
• Understanding of model deployment, monitoring, interpretability, bias, drift, and production lifecycle management.
• Ability to communicate complex analytical concepts, strategy, risk, and outcomes clearly to senior stakeholders.
• Experience operating in an environment where data quality, privacy, security, compliance, and reliability are essential.

Preferred Qualifications

• Master’s degree or PhD in a relevant discipline.
• Leadership experience within healthcare, digital health, health insurance, life sciences, financial services, or another regulated industry.
• Experience supporting digital customer experiences, AI powered products, workflow automation, or clinical decision support.
• Experience with natural language processing or other methods for analyzing unstructured text and customer interaction data.
• Familiarity with Generative AI, large language model evaluation, personalization, recommendation systems, and conversational data products.
• Experience with ontology, semantic models, knowledge graphs, or enterprise data products.

Work Model and Travel

The position is fully remote within the United States and requires occasional travel to Dallas, Texas. Travel is expected no more than once per quarter.

The organization is currently unable to employ candidates residing in California, Hawaii, New York, North Dakota, Oregon, Rhode Island, Washington, or Wyoming.

Work Authorization

Applicants must be permanently authorized to work in the United States without current or future employer sponsorship. Eligible applicants are limited to U.S. citizens and U.S. lawful permanent residents, commonly referred to as green card holders.

Compensation

The anticipated base salary is $265,000 to $300,000 per year, based on experience and qualifications. The position also includes an annual bonus opportunity, healthcare benefits, and a 401(k)-retirement plan.