Cigna is looking for an experienced Data Scientist with extensive predictive Modeling and machine learning experience to join our Data Analytics team which applies advanced Data Science (DS), Artificial Intelligence (AI) and Machine Learning (ML) to produce solutions that drives marketing optimization and sales growth.

Using state of the art AI tools, DS platforms, ML libraries, and optimization tools, we leverage internal, external, online and offline data sources.

The person in this role would be responsible for conducting data analysis and developing predictive models leveraging data science and machine learning to solve various business use cases, including marketing intelligence, customer segmentation, and predictive models for sales and marketing organization. We are looking for a candidate who will support our product, sales, leadership and marketing teams with insights gained from analyzing company and external data.

Who can communicate with others with a statistical mindset, and can conduct exploratory analysis during data preparation and beyond.

The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Responsibilities

• Understand the business problem in Direct to Customer sales of marketing domain to create value for the business, clients, customers and providers, and identify critical questions that can be answered with AI or DS.
• Scrub, clean, prepare, and browse the data: fill in missing data values, determine outliers, regularize and normalize the data (e.g., names), engineer features, and transform it into a more useful form.
• Explore and visualize the data using tools such as Python modules including pandas, matplotlib, bokeh, and Seaborn, Tableau, and Looker.
• Build, evaluate, and document the models
• Generate plausible explanations for presentation to stakeholders and deployment.
• Communicate results and ideas to key decision makers
• Work with data engineers to deploy the models, build data pipelines, and scalable systems.
• Work with stakeholders to identify opportunities for leveraging company data to drive business analytics solutions.
• Research and develop statistical learning models for data analysis
• Identify valuable data sources and automate collection processes
• Undertake preprocessing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms
• Present information using data visualization techniques
• Collaborate with sales, marketing and senior executive teams

Qualifications

• Minimum 5 years of relevant experience in Data Science
• MS/PhD in Computer Science, Math, Statistics, or in any technical field that provides a solid basis for analytics or equivalent work experience
• Excellent understanding/experience with leading machine learning methods such as neural networks, deep learning, KNN, Naive Bayes, SVM, Lasso Regression, Elastic Net Regression, Boosting and Bagging Random Forest, XGBoost, Association Rules, Cross Validation Method, and Unsupervised Learning and their real-world advantages/drawbacks.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience with Hive and database access languages such as SQL and storage platforms such as S3.
• Experience with distributed computing platforms such as Hadoop and Spark is a plus.
• Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Experience using advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Experience using business intelligence tools (e.g. PowerBI, Tableau) and data frameworks (e.g. SAS, Tera Data, Hadoop)
• Strong problem-solving skills with an emphasis on sales and marketing predictive analytics.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Working experience with third-party data sources like Acxiom/Data Axle/Epsilon is preferred.
• Healthcare Insurance and B2C Marketing domain knowledge is highly preferred.
• Medicare, Medicaid or Government sponsored health plan marketing experience/knowledge.

About Cigna

Cigna Corporation exists to improve lives. We are a global health service company dedicated to improving the health, well-being and peace of mind of those we serve. Together, with colleagues around the world, we aspire to transform health services, making them more affordable and accessible to millions. Through our unmatched expertise, bold action, fresh ideas and an unwavering commitment to patient-centered care, we are a force of health services innovation. When you work with us, or one of our subsidiaries, you’ll enjoy meaningful career experiences that enrich people’s lives. What difference will you make?

What difference will you ma