Senior Data Scientist (Service Ops Customer and Digital) - Work at Home

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