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Director, Data Science & Medical Economics 

About the Organization MOBE guides people to better health and more happiness. We help people discover connections between aspects of their lifestyle that affect health and well-being, including their medications and supplements. Behind our innovative solutions are robust data analytics, digital application, and a uniquely human philosophy. With one-to-one connection and compassion, we motivate people to transform their lives.

MOBE is a high-growth organization with a culture built on trust and collaboration and our team is our most significant asset. Supporting and empowering others is at the core of our service and is also the foundation of our culture. We value a workforce made up of people with differences who are eager to learn from each other and grow personally and professionally. We extend this approach to our partners and communities, seeking to increase understanding and expand opportunities across all groups. Go to for more about diversity, equity, and inclusion at MOBE.  

MOBE is seeking an experienced and highly skilled Director to join our team as the leader of Data Science and Medical Economics. This pivotal role will be responsible for driving innovation and providing strategic direction to deliver impactful insights. Your role will require collaboration with cross-functional teams, including medical professionals, business leaders, and IT personnel, to uncover new opportunities and drive data-driven decision-making processes. The Director will be a key player in transforming complex data into actionable intelligence that drives significant improvements in healthcare outcomes and financial efficiency.



  1. Leadership and Strategy:
  • Lead and mentor a team of data scientists, statisticians, and actuaries, fostering a collaborative and high-performing culture.
  • Develop and execute the department's strategic vision, aligning with the overall organizational goals to optimize health outcomes.
  • Establish a roadmap for the data science team, identifying areas for growth and improvement in analytics, predictive modeling, and machine learning.
  • Employ actuarial principles and methodologies to assess financial risks and analyze claims-based data. Lead actuaries to develop models and projections to support pricing and risk management.


  1. Data Analysis and Modeling:
  • Oversee the design and development of statistical models, machine learning algorithms, and predictive analytics to identify causality between medical interventions and outcomes.
  • Utilize big data sets to analyze patterns, trends, and relationships that impact health and financial metrics.
  • Apply common machine learning models, such as linear regression, logistic regression, decision trees, random forests, and gradient boosting, to analyze complex healthcare data.


  1. Technical Proficiency:
  • Possess expertise in programming languages such as Python, R, or SAS, to manipulate, clean, and transform large-scale healthcare datasets for analysis.
  • Experience with DBT and SQL to build and maintain robust data pipelines and facilitate reproducibility and scalability of data processes.
  • Collaborate with Data Operations and Engineering to design data models that are not only effective and efficient but also scalable.


  1. Value Articulation:
  • Develop a clear value articulation strategy, communicating the impact of interventions on health outcomes and claims cost reduction to internal stakeholders and external partners.
  • Collaborate with cross-functional teams, including medical, clinical, and business stakeholders, to define key performance indicators and metrics for measuring success.
  • Lead research efforts to establish causal treatment effect relationships between medical interventions and improved health outcomes, demonstrating the value of interventions to decision-makers.
  • Implement innovative methodologies, such as randomized controlled trials and quasi-experimental designs, to strengthen the causal inferences.


  1. Business Process Optimization:
  • Collaborate closely with business stakeholders to understand their operational processes and challenges related to engagement, retention, and other key performance indicators (KPIs).
  • Utilize data-driven insights and predictive modeling to identify opportunities for process optimization, resource allocation, and cost savings.
  • Provide recommendations and actionable insights to improve business processes and overall efficiency.


  1. Reporting and Presentation:
  • Prepare and present data-driven insights, findings, and recommendations to executive leadership and business stakeholders.
  • Develop compelling visualizations and dashboards to effectively communicate complex data to non-technical audiences, facilitating data-driven decision-making.


Position Requirements


  • Advanced degree (Ph.D., MSc) in Data Science, Statistics, Actuarial Science, Economics, or a related field.
  • Proven track record of at least 8 years in leading data science or actuarial science teams, preferably in the healthcare or insurance industry.
  • Extensive experience in designing and implementing statistical models and machine learning algorithms, using Python, R, or SAS.
  • Demonstrated expertise in causal inference methods, including randomized controlled trials and observational studies.
  • Strong understanding of healthcare economics, medical claims, and health outcome metrics.
  • Excellent leadership, communication, and interpersonal skills, with the ability to work effectively with diverse teams and stakeholders.
  • Business acumen and the ability to leverage data-driven insights to inform strategic decision-making.


Join our dynamic and passionate team in transforming healthcare through cutting-edge data science and medical economics initiatives. As a Director, you will have the opportunity to make a significant impact on the health and well-being of MOBE participants while driving financial efficiency and sustainability. Apply now to be a part of our mission-driven organization.

Full-Time/Part-Time Full-Time  
EOE Statement We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.  
Location Minneapolis  

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