Jobs for People with MS: National MS Society

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.

Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

Seeking a leader to fill a role on the predictive analytics team within the Aetna Commercial Actuarial Department. The ideal candidate will bring knowledge in predictive modeling, data science, and actuarial science within the healthcare industry. With the ability to reframe vague but mission-critical business objectives into empirical problems, you can address them with machine learning and statistical modeling techniques. You will lead strategic development and operational execution of predictive analytics initiatives that drive data-driven decisions, enhance risk assessment, and improve overall financial and health outcomes. This role will involve collaboration across multiple departments including actuarial, underwriting, data science, and IT, to integrate advanced analytics into business processes and support the organizational growth and profitability goals.

As an innovative and strategic advisor

· Develop and execute predictive analytic strategies aligned with the company’s business goals, particularly in risk management and claims management to better understand and accurately price commercial health risk.

· Stay informed on industry trends, emerging technologies, and regulatory requirements to ensure we are both competitive and compliant.

· Influence organization strategy through data-driven insights and predictive modeling.

· Continuously monitor, evaluate, and improve methodologies, processes, and tools to maintain a cutting edge analytics advantage.

​ Predictive modeling and data science acumen

· Lead and guide teams in building, testing, deploying predictive models for various aspects of health insurance such as claims prediction, underwriting, and customer lifetime value forecasting.

· Apply machine learning, AI, and statistical modeling techniques to extract actionably insights from large and complex healthcare datasets.

· Ensure high model accuracy, stability, and performance to support the business.

Joining forces and inspiring trust

· Work closely with actuarial, data science, underwriting, and claims to identify opportunities where predictive analytics can solve business challenges or create new value.

· Partner with IT and data engineering teams to optimize data pipelines and ensure robust data infrastructure to support analytics initiatives.

· Serve as a trusted advisor for senior leadership and stakeholders, presenting insights and recommendations in a clear and actionable manner.

Required Qualifications

· 5+ years of related actuarial work experience

· ASA (Associate of the Society of Actuaries) or FSA (Fellow of the Society of Actuaries)

· Prior healthcare experience

· Strong understanding of commercial health insurance, risk adjustment, underwriting.

· Experience in programming languages such as Python, R, or SQL.

Preferred Qualifications

· Proven knowledge in machine learning, AI, and statistical modeling techniques applied to healthcare and insurance data.

· Experience with cloud computing environments, such as AWS, Azure, or Google Cloud, for model deployment and ability to navigate various Aetna data sources.

· Excellent communication and presentation skills with the ability to explain complex technical concepts to AVP and VP level leaders.

Education

· Bachelor’s degree or equivalent years of experience.

Pay Range

The typical pay range for this role is:

$75,400.00 - $182,549.40

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program.

In addition to your compensation, enjoy the rewards of an organization that puts our heart into caring for our colleagues and our communities. The Company offers a full range of medical, dental, and vision benefits. Eligible employees may enroll in the Company’s 401(k) retirement savings plan, and an Employee Stock Purchase Plan is also available for eligible employees. The Company provides a fully-paid term life insurance plan to eligible employees, and short-term and long term disability benefits. CVS Health also offers numerous well-being programs, education assistance, free development courses, a CVS store discount, and discount programs with participating partners. As for time off, Company employees enjoy Paid Time Off (“PTO”) or vacation pay, as well as paid holidays throughout the calendar year. Number of paid holidays, sick time and other time off are provided consistent with relevant state law and Company policies.

For more detailed information on available benefits, please visit Benefits | CVS Health (https://jobs.cvshealth.com/us/en/benefits)

We anticipate the application window for this opening will close on: 12/30/2024

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

We are an equal opportunity and affirmative action employer. We do not discriminate in recruiting, hiring, promotion, or any other personnel action based on race, ethnicity, color, national origin, sex/gender, sexual orientation, gender identity or expression, religion, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.