Senior Data Scientist (Service Ops Customer and Digital) - Work at Home at Cigna in Bloomfield, Connecticut

Job Description:

Summary

Our team leverages advanced Data Science (DS), augmented intelligence (AI) and machine learning (ML) to help better predict our customers' health outcomes, advance affordability, quality and accessibility of healthcare. We are recognized as a leader in leveraging Data & Analytics capabilities to create value for customers and stakeholders, enabling better decision making and health outcomes. 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.

As a Sr. Data Scientist, you will be working on both structured and unstructured data to build ML applications to support various healthcare-related business use cases that will improve our health system. Your work will require deep acquaintance with Evernorth's data, seeking to find ways to deliver value through advanced feature engineering. From your models, you will deliver actionable insights that can be incorporated into existing Cigna wellness products as well as new programs. In addition to collaborating with Data Science Management to establish strategic priorities, you will work closely with Data & Engineering to deliver code that is robust and ready to scale.

The ideal candidate for this role will have strong coding skills (preferably in Python, PySpark), strong knowledge about ML algorithms and NLP techniques, a passion for creating technology to improve the healthcare systems, and an attitude of creativity and continual learning.

Responsibilities

• Create models using NLP, ML / AI techniques to predict risk/cost and identify actionable insights


• Deliver clean, reusable, and scalable code


• Work closely with Data & Engineering to deploy models


• Provide thought leadership on the latest analytic techniques, technologies, and methods

Qualifications

• 5+ years' of industry experience related to Data Mining, Statistical Analysis, ML Algorithms, Gen-AI and NLP Techniques


• Strong experience with Python and its data science libraries such as Scikit-learn, Pandas, Numpy, and Keras


• Strong understanding of NLP techniques such as information extraction, sentiment analysis, text summarization, and topic modeling


• Strong understanding of ML/AI methods such as SVM, Random Forest, XGBoost, Light GBM, Deep Learning (CNN, RNN, LSTM), Reinforcement Learning, Optimization


• Strong programming experience including understanding of concepts in data structures, algorithms, and software engineering principles


• Good understanding and experience with traditional data science approach like sampling techniques, feature engineering, classification, and regression.


• Have experience in building forecasting model for trend analysis


• Excellent oral and written communication skills


• Prior experience working in the healthcare industry is highly desirable


• Experience with deploying advanced natural language models and time-series model into production is highly desirable


• MS/PhD in Computer Science, Math, Statistics, or in any technical field that provides a solid basis for analytics or equivalent work experience

If you will be working at home occasionally or permanently, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload.

For this position, we anticipate offering an annual salary of 121,400 - 202,400 USD / yearly, depending on relevant factors, including experience and geographic location.

This role is also anticipated to be eligible to participate in an annual bonus plan.

We want you to be healthy, balanced, and feel secure. That's why you'll enjoy a comprehensive range of benefits, with a focus on supporting your whole health. Starting on day one of your employment, you'll be offered several health-related benefits including medical, vision, dental, and well-being and behavioral health programs. We also offer 401(k) with company match, company paid life insurance, tuition reimbursement, a minimum of 18 days of paid time off per year and paid holidays. For more details on our employee benefits programs, visit Life at Cigna Group .

About The Cigna Group

Doing something meaningful starts with a simple decision, a commitment to changing lives. At The Cigna Group, we're dedicated to improving the health and vitality of those we serve. Through our divisions Cigna Healthcare and Evernorth Health Services, we are committed to enhancing the lives of our clients, customers and patients. Join us in driving growth and improving lives.

Qualified applicants will be considered without regard to race, color, age, disability, sex, childbirth (including pregnancy) 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 reasonable accommodation in completing the online application process, please email: SeeYourself@cigna.com for support. Do not email SeeYourself@cigna.com for an update on your application or to provide your resume as you will not receive a response.

The Cigna Group has a tobacco-free policy and reserves the right not to hire tobacco/nicotine users in states where that is legally permissible. Candidates in such states who use tobacco/nicotine will not be considered for employment unless they enter a qualifying smoking cessation program prior to the start of their employment. These states include: Alabama, Alaska, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maryland, Massachusetts, Michigan, Nebraska, Ohio, Pennsylvania, Texas, Utah, Vermont, and Washington State.