Senior Data Scientist

Premier Inc.

10d•$90,000 - $150,000•Remote

About The Position

The Senior Data Scientist is a Subject Matter Expert that advises on both structured and unstructured analytic models to solve complex data problems in a way that ensures consistency, reusability, and quality across the organization. This position will have responsibility for the development, delivery, enhancement, integration, integrity, maintenance, and support of the operation of information technology (IT) infrastructure, data, products, solutions, and services to support client operations and business activities. This position will be a senior individual contributor and subject matter expert for strategic initiatives around data exploration, data analysis, and complex, high dimensional datasets. Areas of focus include Data Modeling, Application Methodology Development, and AI, Machine Learning, and statistical modeling.

Requirements

4 or more years of applicable experience.
Bachelors degree (Required).
Statistical Models: probabilistic and predictive statistical models including multiple regression, t-tests, z-tests, log modeling, Naïve Bayes and Monte Carlo Simulation (using R or Python).
Clinical Data: UB and 1500 claims, HL7, CDA, EHR, etc. and standard healthcare taxonomies.
Data Analysis: advanced querying techniques (ad hoc, ETL, and 3-tier application context), Oracle, DB2, Postgres, SQL Server & Netezza.
Health care research experience, with large patient data sets.
Statistical methodology Design/development.
Data analytics and standardization.
Consulting and Conflict Management.
Remain in a stationary position for prolonged periods of time.
Be adaptive and change priorities quickly; meet deadlines.
Attention to detail.
Operate computer programs and software.
Ability to communicate effectively with audiences in person and in electronic formats.
Day-to-day contact with others (co-workers and/or the public).
Making independent decisions.
Ability to work in a collaborative business environment in close quarters with peers and varying interruptions.

Nice To Haves

Master’s degree

Responsibilities

Collaborates with Data Science leadership, Product Management, Development, and Research teams in the creation and implementation of machine learning algorithms and statistical models.
Leads the design and implementation of complex data solutions across teams while maintaining consistency within Premier methodology (e.g. prediction, probabilistic data matching, identifying outliers, confidence scoring, etc.).
Work with developers and architects to translate prototypes into new products, services, and feature, and provide guidelines for large scale implementation.
Use a flexible, analytical approach to design, develop, and evaluate predictive models, ML, AI, NLP and advanced algorithms that lead to optimal value extraction from the data.
Produce innovative solutions driven by exploratory data analysis from complex and highly dimensional datasets.
Serves as a subject matter expert within various business domains (Cost, Clinical, MDM, etc.).
Participate in data exploration and conceptual design for strategic initiatives.
Apply knowledge of statistics, artificial intelligence, machine learning, programming, data modeling, simulation and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Generate and test hypotheses and analyze and interpret the results of product experiments.
Acts as an active member of the team throughout the design and implementation of the solution.
Participate in build vs. buy decisions with outside vendors as it relates to analytic-based solutions.
Facilitate & lead meetings with the business/customers and IT teams in order to gather and document requirements.
Analyze business requirements, procedures and problems, to design solutions and make recommendations.
Develop features and stories based on requirements to feed product backlogs.
Conduct impact assessments across all existing applications, integration and data warehouses resulting from the solution implementation.
Provide data, data relationships, and data science practice advice, demonstrations and presentations to colleagues, clients, and management. Conduct research, as needed.
Provide mentoring and training.
Develop project estimates and work plans.
Identifying, developing, reviewing, and evolving best practices, standards, operating procedures, and processes.
Participating in the review of team member deliverables.