Senior Data Scientist-Machine Learning 



Are you looking to have meaningful and major impact of your data science work? Are you tired of working on toy machine learning problems involving flower petal lengths?  Cigna is ramping up its data science team to help improve the lives of its customers by leveraging terabytes of data.  This is an unprecedented opportunity to get in on the early stage of that growth and make a real difference in the lives of people.

Cigna is not only committed to quality service for its customers, but is committed to building a world-class environment to develop, test, and deploy data science solutions. The current data science team is diverse in scope, background, and application—right now, the application areas are virtually unlimited: anything that can have a positive impact on customers by leveraging data. Furthermore, the ideal candidate can take advantage of remote working possibilities to focus on producing results. More than geographic location, we are looking for top data scientists who can deliver insightful outcomes to our stakeholders using state-of-the art prototyping environments.

Cigna has recognized that data scientists are not only in demand, but are part of a rapidly changing field. As a result, Cigna has created a Data Scientist Personal Growth Program to create flexibility and granularity within a data scientist’s personal growth and changing roles. These roles and associated development opportunities facilitate personal development in a way that benefits both Cigna and the data scientist.


We are looking for a Data Scientist to apply and develop new machine learning methods that can help unlock the knowledge hidden in our data, combine it with other data, to help make better decisions for our customers.  The scope of the projects can vary from automating a manual process to improving an existing automated process with data: recommendation systems, automated scoring, predicting of clinical outcomes, anomaly detection, organizing information for presentation.  The primary focus is on delivering high-speed, high-quality data science systems that can be integrated into current or new products.


  • Obtain data from internal sources using state of the art big-data tools such as Teradata and Hive.
  • Combine and Augment the Data with data from external sources.
  • Scrub, clean, prepare, and browse the data: fill in missing data values, determine outliers, regularize and normalize the data (e.g., names), transform it into a more useful form (e.g., time series).
  • Explore and visualize the data using tools such as Python modules including pandas, matplotlib and Seaborn, Tableau, and Looker. Select appropriate features that optimize performance.
  • Build models using state of the art machine learning methods such as Cloudera’s Data Science Workbench and Data Robot.
  • Evaluate the results using performance metrics.
  • Interpret, visualize, and present the results to stakeholders.
  • Work with data engineers to deploy the models.
  • Develop processes and tools to monitor the models’ performance after deployment.


  • BS/MS/PhD in Computer Science, Math, Statistics, or in any technical field that provides a solid basis for analytics highly desired.
  • Excellent understanding/experience with machine learning methods such as neural networks, deep learning, KNN, Naive Bayes, SVM, Lasso Regression, Elastic Net Regression, Boosting and Bagging Random Forest, Association Rules, Cross Validation Method, and Variable Clustering.
  • Experience with Python’s data science toolkits such as Scikit-learn, pandas, Numpy and Seaborn through Jupyter or iPython notebooks.
  • Experience with data visualization tools such as Python modules including matplotlib, Seaborn, bokeh, Tableau, and Looker.
  • Experience with Hive and database access languages such as SQL. Experience with Hadoop and Spark is a plus.
  • An understanding of probability distributions and basic statistics.
  • Minimum 2-3 years of experience programming in Python to clean and transform data
  • Intellectual curiosity and internal motivation (e.g., projects you’ve done outside of being paid or in school).
  • A data-driven personality (as opposed to a theory-driven personality).

Qualified applicants will be considered for employment without regard to age, race, color, religion, national origin, sex, sexual orientation, gender identity, disability, veteran status. Need an accommodation? Email:

Primary Location: United States-Work From Home Jobs

Job: Bus Ops–Operations Mgmt (Bus)

Work at home opportunity (External):Yes

Schedule: Full-time

Shift: Day Job

Employee Status: Regular

Job Type: Standard

Job Level: Individual Contributor

Travel: No

Job Posting: Dec 14, 2017, 1:53:43 PM