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Cigna Corporation (NYSE:CI) and its subsidiaries comprise a global health services and financial company that serves millions of people worldwide through our health, pharmacy, behavioral, dental, disability, life, accident and international products and services. Our mission is to help improve the health, well-being and peace of mind of the people we serve.
At Cigna we leverage advanced data science (DS), artificial intelligence (AI) and machine learning (ML) through the use of centralized centers of excellence to help better predict our customers’ health outcomes, advance affordability, quality and accessibility of the healthcare. This allows us to harness insights from the millions of lives we serve, helping our patient advocates and clinicians service our customers, ensuring they receive the best care from the highest performing medical providers. The speed in which DS, AI and ML are advancing means we are continuously learning and evolving our advanced data science capabilities. Cigna’s Global Data & Analytics (GD&A) unit offers solutions that provide actionable insights to internal and external business partners and customers that help reduce health costs, improve outcomes, provide financial security and measure and forecast business performance.
The role of Director of Data Science is an opportunity for a proven leader in the field to set and execute a vision for advancing analytics, leading Cigna to achieve our growth goals. Reporting to the Head of Data Science, the Director is responsible for leveraging large internal and third party data and enabling optional facts-based decision making and operational processes at the point of care. The Director will provide both strategic and technical leadership and direction for data scientists and will assess the organization's analytical methods, tool selection, talent acquisition, and development strategy. This leader’s work will revolve around understanding complex business problems in health systems, large and complex data manipulation, model development, validation and deployment and ensuring model documentation provides full model transparency. This leader will be responsible for building and refining supervised and unsupervised statistical and machine learning models to improve insights, enhance data-driven business strategies, and drive improved profitability.
- Align between complex business problems in healthcare and advanced quantitative techniques in statistical analysis, predictive modeling and machine learning.
- Collaborate with business analytics partners to identify appropriate modeling techniques.
- Propose and utilize appropriate quantitative methods addressing a diverse set of considerations in data quality, model interpretability, regulatory, operational constrains and other.
- Evaluate and compare benefits and limitations of alternative approaches, optimize model performance.
- Translate multi-year use case roadmaps into sets of structured, rigorously solved model development modules.
- Lead model development, inclusive hands-on development, while being assisted by junior data scientists. Execute full stack model development process - data collection, aggregation, analysis, visualization, productionalization and monitoring performance of Data Science models.
- Focus on continuous learning and technical skill development through knowledge of the new applications and methods.
- Search for practical commercialization of innovative technologies to align between business value and tested ability to deliver incremental performance and impact.
- Evaluate, compare, and apply innovative quantitative research tools and models to answer complex healthcare questions and build solutions to decisions with large impact to profitability.
- Present, discuss and debate the team's work and resulting recommendations in an enthusiastic and defendable way.
- Contribute to evolving infrastructure to extract, manage, and analyze data in a scalable way, and making use of this data to improve affordability and quality of healthcare solutions.
- Execute the talent strategy required to achieve meet business needs. Management entails providing individual and team leadership to the data science team and ensuring they are growing their capabilities and achieving their career goals.
- Significant prior experience as a Data Science Manager leading sizable teams, working on challenging problems at scale, in the Industry setting.
- Strong preference for healthcare experience; additional industries (financial services, consumer industries, digital) considered through candidate’s ability to identify transferable learnings and synergies.
- Strong desire to solve complex problems with scientific rigor at scale, understanding the value derived from getting results early and iterating.
- Advanced level proficiency with statistical and machine learning modeling techniques such as regression, decision trees, boosting algorithms, neural networks, supervised/unsupervised clustering techniques and experimental test design. Experience with NLP / text mining, graph analytics and image recognition techniques a plus.
- Applied hands-on skills in developing predictive models in big data environments (Hadoop, Pig, Scala), development experience with the scientific Python stack (Pandas, Numpy/Scipy, scikit-learn, scikit-image etc.), knowledge of statistical software such as R, Julia etc.
- Experience with types of tools such as H2O, TensorFlow, Bayesia, Keras, ability to acquire working knowledge of the new tools.
- Experience in developing predictive models within distributed computing platforms such as Hadoop, AWS, Azure, GCP.
- Ability to work with complex, multi-system medical data that requires extensive wrangling and cleanup. Experience with mining authorization and medical management data for process improvement opportunities and expertise and managed care clinical data (e.g. claims, labs, Rx) is a plus.
- Superior analytical skill combined with business discipline. Ability to perform insightful and actionable quantitative analysis.
- Ability to manage multiple complex projects while meeting all deadlines,
- Ability to manage people to achieve optimal results.
- Strong interpersonal skills plus an outstanding ability to build relationships and navigate within a complex organization. Self-awareness, maturity, ability to collaborate as part of the multi-disciplinary team.
- PhD in Quantitative fields such as Mathematics, Decision Science, Operational Research, Computer Science, Economics, Statistics, Engineering or similar fields strongly preferred. Generally requires 10+ years related experience.
Qualified applicants will be considered without regard to race, color, age, disability, sex (including pregnancy), childbirth or related medical conditions including but not limited to lactation, sexual orientation, gender identity or expression, veteran or military status, religion, national origin, ancestry, marital or familial status, genetic information, status with regard to public assistance, citizenship status or any other characteristic protected by applicable equal employment opportunity laws.
If you require an accommodation based on your physical or mental disability please email: SeeYourself@cigna.com. Do not email SeeYourself@cigna.com for an update on your application or to provide your resume as you will not receive a response.