Cotiviti is currently looking to add an industry leading Data Scientist II, who is focused on machine learning solutions to join our Enterprise Data Science Team and build value-oriented, production level machine learning solutions.  This role is not for research-oriented data scientist, but rather should be of interest to those that want to apply their knowledge and experience to real world healthcare problems and seek to utilize machine learning and artificial intelligence to reduce the cost of healthcare and improve the management of healthcare. With access to dedicated on premise and cloud based big data solutions, this role will work with a vast amount of structured and unstructured data, including claims, membership, provider, medical records, and additional data sources, to begin to solve some of the most pressing healthcare issues of today.  A Data Scientist III at Cotiviti will be given the opportunity to work directly with a team of knowledge healthcare professionals to set and establish aggressive goals and execute them with the team. This role is for an ambitious and curious technologist, with the flexibility and personal drive to succeed in a dynamic environment where they are judged based on their direct impact to business outcomes.

As a Data Scientist II within Cotiviti you will be responsible for delivering solutions that help our clients and internal partners identify payment integrity issues, reduce the cost of healthcare processes, or improve the quality of healthcare outcomes. You will work as part of a team and will be individually responsible for the delivery of value, through machine learning, associated with your projects. You will be expected to follow processes and practices that allow your models to be incorporated into Cotiviti’s machine learning platform for production execution and monitoring. You will have more flexibility to experiment during exploratory data analysis to discover solutions to business problems.

• Work with key stakeholders with Research and Development, as well as Operations, along with product management to access the potential value and risks associated with business problems that have the potential to be solved using machine learning and artificial intelligence techniques.
• Develop an exploratory data analysis approach to verify the initial hypothesis associated with potential use cases.
• Document your approach, thinking, and results in standard approaches to allow other data scientists to collaborate with you on this work.
• Prepare your final trained model and develop a validation set for QA
• Work with production operations to deploy your model into production and support them in monitoring model performance.
• Participate in other data science teams collaborating with your peers to support their projects.
• Participate in knowledge sharing sessions to bring new insights and technologies to the team.
• Participate in design sessions to continuously develop and improve the Cotiviti data science platform.
• Provide end-to-end value-based solutions, including data pipelines, model creation, and application for end user consumption.

• Applied Machine Learning: Application of a variety of machine learning techniques to increase identification of payment integrity issues for our clients, reduce the cost of auditing processes or increase the quality of care and outcomes.  Must have implemented machine learning solutions within production environments at scale
• Big Data Analysis: Strong ability to manage and analyze data in a Big Data environment using a variety of scripts, potentially including but not limited to Scala/Spark and Python as well as Cloud based Artificial Intelligence/Machine Learning capabilities. 
• Reasoning and Problem Solving: Ability to actively and skillfully conceptualize, apply, analyze, synthesize, and/or evaluate information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action
• Consulting: Demonstrated ability to make and gain acceptance of data-driven recommendations made to business owners. Strong ability to appropriately summarize and effectively communicate complex concepts & varied data sets to inform stakeholders, gain approval, or prompt actions; Applies to multiple audiences ranging from the analyst to executive level; Includes oral & written communication and multimedia presentation
• Statistical Analysis: Apply statistical methodology to solve business problems; appropriately interprets meaning from results
• Business Knowledge: Good understanding of the tenets of health insurance, the managed care model, industry coding/policy standards, the claim adjudication process, and issues related to fraud waste and abuse. Ability to apply this knowledge to the development & evaluation of new initiatives and support leading the team strategy toward best practices.
• Financial Analysis: Ability to understand, generate and evaluate healthcare utilization, unit cost and medical cost trends. This includes understanding levers that effect healthcare cost, such as contracting, networks, policies, benefit structures, and product design. Ability to draw conclusions and make recommendations based on financial data
• Functional Programming: Ability to work with, understand and create object oriented/functional programming solutions using modern application frameworks. 

Minimum Qualifications:

• Master’s or PhD degree in relevant discipline (Statistics, Mathematics, Computer Science, etc.) or commensurate professional experience
• 5+ years of experience (or recent Masters+ graduate) in advanced statistics analytics
• 5+ years of experience (or recent Masters+ graduate) in Big Data environments
• 3+ years of experience (or recent Masters+ graduate) developing machine learning models from novel datasets created in a commercial data science environment and working with others to develop production ready versions of models that are deployed within operational environments, and tracking model impact post deployment
• Ability to build machine learning models with minimal supervision from manager/team lead
• 5+ years of experience with SQL; ability to write SQL queries efficiently extract data from SQL Server, Oracle, and Hive
• 5+ years of experience using Python, R, and/or Scala
• 3+ years of experience (or recent Masters+ graduate) using distributed frameworks, such as Spark
• 3+ years of experience (or recent Masters+ graduate) using machine learning frameworks, such as Scikit-learn
• Ability to work independently, as well as collaborate as a team
• Flexibility to work with global teams, as well as geographically dispersed US based teams
• Professional with the ability to properly handle confidential information
• Be value-driven, understand that success is based on the impact of your work rather than its complexity or level of effort.
• Ability to handle multiple tasks and meet deadlines
• Ability to work within a matrixed organization
• Proficiency in all required skills and competencies above
• Ability to demonstrate modeling prowess through one or more assessments

Additional Beneficial Requirements

• Knowledge or experience of DevOps lifecycle tools like GitHub/BitBucket, Jenkins, Jira
• Knowledge or experience of the health insurance industry in the United States
• Commercial experience in deep learning frameworks, such as Pytorch
• Commercial experience in Generative AI
• Commercial experience with NLP
• Commercial experience with AWS, Azure, GCP, OCI, and/or Databricks

Base compensation ranges from $108,000.00 to $135,000.00. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.

Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our Careers page.

Date of posting: 9/16/2024

Applications are assessed on a rolling basis. We anticipate that the application window will close on 12/17/2024, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.

Since this job will be based remotely, all interviews will be conducted virtually. 

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