Sr. Data Scientist

The Senior Data Scientist at MedeAnalytics is responsible for producing innovative solutions through exploratory data analysis from complex and high-dimensional data sets. They will utilize their skills in statistics, data modeling, advanced mathematics, and programming to design, develop, evaluate, and deploy robust solutions using data science, machine learning, and predictive modeling techniques. The Senior Data Scientist will collaborate with product teams and clients to translate real-world healthcare issues into well-defined problem statements and requirements, and will be involved in data cleaning and exploration, feature engineering, model development, model deployment, and model documentation.

Collaborate independently with product teams and clients to translate real-world healthcare issues into well-defined problem statements and requirements to build out mathematical frameworks and data science solutions.

Select appropriate datasets and data representation methods.

Process, cleanse, and verify the integrity of data used for analysis and modeling.

Use strong programming skills to explore, examine, and interpret large volumes of data in various forms.

Develop data structures and pipelines to organize, collect, and standardize data used in data science workflow.

Select influential features, as well as develop additional features, using machine learning techniques for use in model development.

Design, develop, and validate data models and algorithms used for prediction, classification, pattern detection, and other insights related to healthcare issues.

Develop documented, maintainable code.

Develop and utilize unit tests to validate functional correctness and completeness, verify correct error handling, check input/output data, optimize performance, and identify and fix defects.

Deploy and deliver AI/ML products as embedded algorithms into existing products or deploy them into production as microservices.

Work closely with product development teams to design, build, manage, and test APIs.

Collaborate with product teams and engineers to coordinate the implementation and QA of algorithms and other data science solutions.

Continued evaluation and maintenance of models throughout their lifespan.

Document projects including problem definition, data gathering and processing, detailed set of results, and a

Exceptional skills in statistics, data modeling, advanced mathematics, and programming

Ability to collaborate independently with product teams and clients to translate real-world healthcare issues into well-defined problem statements and requirements

Strong programming skills to explore, examine, and interpret large volumes of data in various forms

Experience in data cleaning, data exploration, and data verification

Knowledge of machine learning techniques for feature engineering and model development

Ability to design, develop, and validate data models and algorithms used for prediction, classification, pattern detection, and other insights related to healthcare issues

Experience in deploying AI/ML products as embedded algorithms into existing products or as microservices in production

Proficiency in documenting projects, including problem definition, data gathering and processing, detailed set of results, and analytical metrics

Strong communication skills to effectively present analytical results and findings to all levels of the organization

Experience in peer reviewing data science code and providing mentorship and guidance to other members of the data science team

Degree with a quantitative element (e.g. mathematics, statistics, computer science) is preferred

• Base Salary Range: USD $100,000 - $150,000
• Individual compensation packages based on various factors unique to the candidate
• Opportunity to make an impact doing work that matters
• Joining a company that deeply values committed, inspired, and passionate employees
• Opportunity for growth and mentorship within the data science team
• Collaboration with cross-functional teams
• Opportunity to work with cutting-edge technologies and tools such as Python, Jupyter Notebooks, Pandas, Numpy, Scikit-Learn, Flask, Gunicorn, Amazon Sagemaker, Oracle, SonarQube, Docker, Postman, REST APIs, Vertica, and MongoDB
• Opportunity to build presentations, dashboards, and reports to effectively communicate analytical results
• Opportunity to present findings to all levels of the organization, including peers, senior management, and customers
• Opportunity to share best practices and approaches for statistics, machine learning techniques, data modeling, simulation, and advanced mathematics
• Proficient understanding of Git
• Knowledge of health care terminology and experience working with payer and provider data preferred