Data Scientist

The Data Scientist II - Generative AI will apply knowledge and experience to real world problems and seek to utilize their skills to reduce the cost of healthcare and improve health quality and outcomes. With access to dedicated premise and cloud based big data solutions, the team can work with a vast amount of structured and unstructured data including claims, membership, physician demographics, medical records and others to begin to solve some of the most pressing healthcare issues of our time. A Data Scientist at Cotiviti will be given the opportunity to work directly with a team of healthcare professionals including analysts, clinicians, coding specialists, auditors and innovators to set aggressive goals and execute on them with the team. This is for an ambitious technologist, with flexibility and personal drive to succeed in a dynamic environment where they are judged based on their direct impact to business outcomes.

Required Skills -

Work with key stakeholders within Research and Development as well as Operations, along with product management, to assess 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 Artificial Intelligence / Machine Learning 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 test 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.

Job Duties -

As a Data Scientist II within Cotiviti you will be responsible for delivering solutions that help our clients 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 associated with your projects. You will be expected to follow processes and practices that allow your models to be incorporated into our machine learning platform for production execution and monitoring. However, initial exploratory data analysis allows for more flexible experimentation to discover solutions to the business problems presented.

Job Requirements -

Work with key stakeholders within Research and Development as well as Operations, along with product management, to assess 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 Artificial Intelligence / Machine Learning 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 test 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 machine learning platform.

Provide End to End value-based solutions, including data pipeline, model creation and application for end user consumption.

Desired Skills & Experience -

Graduate degree in a quantitative discipline such as Computer Science / Engineering, Statistics, Operations Research.

5 years of hands-on data science experience, using typical machine learning and data science tools including pandas, scikit-learn, keras, nltk, and TensorFlow / PyTorch, GPU.

2 years of data science ML experience with PHD degree and 5 years of data science ML experience with master's degree.

Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring / benchmarking and deploying LLMs with tools such as Hugging Face, Lang chain, LLAMA / Mistral and OpenAI, vector databases.

Experience with Embeddings, finetuning, text processing and custom model development.

Experience building production-grade machine learning deployments on AWS, Azure, or GCP.

Designing the solution for ML and Gen AI based use cases.

Experience working with Apache Spark and large-scale distributed datasets.

Experience communicating technical concepts to non-technical and technical audiences is a plus.

Passion for collaboration, learning it all mindset and driving value with AI.

Ability to work independently as well as collaborate as a team.

Flexibility to work with global teams as well geographically dispersed US based teams.

Professional with 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 the level of effort.

Ability to handle multiple tasks, prioritize and meet deadlines.

Ability to work within a matrixed organization.

Proficiency in all required skills and competencies above.

Required Skills : Data Warehouse

Basic Qualification :

Additional Skills :

Background Check : No

Drug Screen : No