Website Express Scripts
The DS COE Sr. Data Scientist will develop and manage relationships and deliverables with vertical partners and/or business stakeholders, IT and data engineering partners and deliver projects and tasks on time and with high quality. You will partner with the Customer Personalization, Servicing Operations and Marketing Analytics teams and other business and operational stakeholders to understand the business context, gather requirements and develop predictive and machine learning models, as well as build broader data science solutions, processes and capabilities. The DS COE team members support and work across the other Cigna verticals due to the customer dimension being a key part of the other verticals and work within both Waterfall and Agile project management approaches to productionize data science solutions. Your work will require deep acquaintance with Cigna’s data and various external data, seeking to find ways to deliver value through advanced feature engineering and rigorous methodologies. From your models you will deliver actionable insights and solutions that can be incorporated into Cigna products and services. You will be supporting all new and existing GD&A-owned models in support of the visions and strategies established by the Data Science Manager and Solution Director.
- Provides expert content/professional leadership on complex Data Science assignments/projects. Develops ML and statistical models and methodologies to predict, classify, quantify, and/or forecast business metrics that help stakeholders make sound business decisions.
- Previous working experience of health care data, particularly claims.
- Develop, evaluate and document the models. Deliver clean, reusable, and scalable code.
- Responsible for the extraction and analysis of all customer personalization related information. Conduct data cleaning, feature engineering, and transformation into a more useful form. Scrub, clean, prepare, and browse the data, fill in missing data values, determine outliers, regularize and normalize the data, engineer features. transform data into useful model features and choose the appropriate modeling algorithm and hyperparameters.
- Passion for creating ML technology and ownership for delivering DS solution to improve health care, with an attitude of creativity and continual learning, be highly motivated, flexible and embrace change.
- Hands-on experience of predictive analytics and ML model development for health care customer personalization, full breadth knowledge of customer outreach campaign effectiveness and product optimization.
- Emotionally intelligent, highly motivated, an excellent communicator (written and verbal) and a team player who can communicate effectively to business and technical audiences at the appropriate levels
- Explore and visualize the data using tools such as Python modules including pandas, matplotlib, bokeh, and Seaborn, Tableau, and Looker.
- Understand the business problem in customer personalization, translate to sound analytical design and data science framework, in order to create value for the business, customers, clients, and identify critical questions and actionable insights that can be answered with Data Science solutions.
- Hands-on programming experience with Hive and database access languages such as SQL and storage platforms such as S3.
- Predictive analytics and ML model development for customer personalization including next best actions are highly desired.
- Proficiency, understanding and experience with leading machine learning methods including Supervised and Unsupervised Learning, such as KNN, Naïve Bayes, linear and non-linear regression, Logistic Regression, SVM, Lasso Regression, Elastic Net Regression, Boosting and Bagging, Random Forest, XGBoost, Association Rules,
- Cross Validation Method, Ensemble methods, forecasting, neural networks, deep learning, optimization.
Qualification & Experience:
- Experience with distributed computing platforms such as Hadoop, Spark, MapReduce, and Yarn, is a plus.
- Masters or PhD or equivalent work experience in Data Science, Engineering, Computer Science, Math, Statistics, or other quantitative fields that provide sufficient data science foundations.
- 5 – 7 years’ hands-on programming experience with the following: Python and its data science libraries such as Scikit-learn, Pandas, Keras, NLTK, Numpy and Seaborn, through Jupyter notebook or Analytic Platforms like Domino. R, DataRobot.
- Working experience with web analytics data (Adobe), call center and digital data.
- Previous working experience in medical claims, Rx claims, dental claims and healthcare industry is highly desired.
Company: Express Scripts
Vacancy Type: Full Time
Job Location: New York, NY, US
Application Deadline: N/A