Company Description:

Healthcare providers and payers across the U.S. and U.K. trust MedeAnalytics to provide actionable insights that enable them to make even smarter decisions in today's new healthcare economy.

With a sole focus on healthcare, we were the first to market in 1994 with a healthcare analytics SaaS solution. Today, that spirit of innovation continues with a platform that includes advanced analytics technologies like machine learning, guided analysis, and predictive analytics. Most recent innovations include a platform-as-a-service offering that enables our clients to build their own applications.

With these technologies and decades-long healthcare expertise, we help more than 1,500 provider and payer organizations achieve better outcomes by unlocking the potential of their data.

Company Mission

Empowering healthcare organizations to make even smarter decisions

Company Vision

The smartest healthcare for everyone

Company Values

Current Role & Growth Opportunity:

The Senior Data Scientist will produce innovative solutions driven by exploratory data analysis from complex and high-dimensional data sets. The Senior Data Scientist uses a flexible, analytical approach to design, develop, evaluate, and deploy robust solutions leveraging innovations in data science, machine learning, and predictive modeling techniques. To do this job successfully, you need exceptional skills in statistics, data modeling, advanced mathematics, and programming. The Senior Data Scientist should be able to independently complete responsibilities. 

Essential Duties and Responsibilities:

• Problem Definition
  • 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. 
• Data Cleaning and Exploration
  • 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
• Feature Engineering
  • Select influential features, as well as develop additional features, using machine learning techniques for use in model development.
• 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, checking input/output data, optimize performance, and identify and fix defects.
• Model Deployment
  • Deploy and deliver AI/ML products as embedded algorithms into existing products or deploy 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.
• Model Documentation
  • Document projects including problem definition, data gathering and processing, detailed set of results, and analytical metrics.
• Communication of Results
  • Use data visualization techniques to build presentations, dashboards, and reports to effectively communicate analytical results which drive insight, recommendations, and solutions.
  • Present compelling, validated findings from exploratory and predictive data analysis to all levels of organization, including peers, senior management, and customers.
• Mentorship
  • Peer review data science code and other product artifacts to ensure technical, logical, and procedural correctness. Validate assumptions and review for hidden biases.
  • Serve as a resident data expert and share best practices/approaches for statistics, machine learning techniques, data modeling, simulation, and advanced mathematics. 
  • Provide mentorship and guidance to other members of the data science team.
• All other duties as assigned.

Essential Education, Experience and Interests:

• Degree with a quantitative element (e.g. mathematics, statistics, economics, engineering, computer science, applied math, etc.) or 5+ years equivalent job experience.
• Strong proficiency with Python, Jupyter Notebooks, and standard Python data science libraries including, but not limited to: Pandas, Numpy, and Scikit-Learn
• Demonstrates proficiency in several areas of data modeling, machine learning algorithms, statistical analysis, data engineering, and data visualization. 
• Experience with cross functional collaboration and project ownership.
• Experience building microservices, preferably using Flask and Gunicorn.
• Strong communication competencies to include presentations and delivery of complex quantitative analyses in a clear, concise, and actionable.
• Proficient understanding of Git.
• Knowledge of health care terminology. (e.g. HRGs, diagnosis / procedure codes, etc.) Experience working with both payer and provider data preferred.
• Experience with SonarQube, unittest, coverage, and nosetests for code quality testing preferred.
• Experience with Docker, Postman, REST APIs preferred.
• Experience with Vertica, MongoDB preferred.

Preferred Experience:

• Must be accountable for individual responsibilities while working collaboratively with data science, product, and engineering teams to achieve project deliverables.
• Passionate about continuously learning and sharing knowledge with others.
• Excellent team-player attitude, with ability to consistently demonstrate the highest levels of professionalism, integrity, mutual respect, and accountability to others.
• Strong analytical and judgment skills, with the ability to make sound decisions and follow through.
• Commitment to thorough testing, documentation, and maintainability of code and research.
• Attentiveness to details and ability to understand and explain both big picture and “in the weeds” views of projects.
• Must be self-motivated, proactive, and willing to ask questions.

Working Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee regularly works near office equipment (telephone, computer) and other employees. The employee works in normal office conditions where there is no physical discomfort due to temperature, dust, noise, etc. Verbal and written communication, telephone usage, filing, sitting, typing, driving, reading and carrying required to perform the essential functions of this job.

Mede/Analytics is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age or protected veteran status.

MedeAnalytics does not utilize any outside vendors/agencies.  Please no unsolicited phone calls or invites.