Sr. Data Scientist

Position: Sr. Data Scientist

Location: San jose, CA or Wisconsin

JD:

The Sr. Data Scientist is driven by an interest in solving complex problems through data exploration, model building and building data products. They are highly analytically minded and have a robust technical tool kit. They are a mid-career professional with portfolio of modeling experience in industry (preferably healthcare sector). The Sr. Data Scientist will be responsible for executing all steps in the analytic process to produce high quality, production ready ML models. They will work with a team of Data Scientists & Analysts to support the development of processes and technologies to improve patient outcomes. This role is responsible for extracting, managing, and analyzing complex administrative healthcare data and applying ML/AI concepts to uncover opportunities for product development.

Responsibilities:

Design and develop Machine Learning & Statistical Models (using R & Python), and other data analysis techniques to collect, explore, and extract insights from structured and unstructured electronic health record data

Build and advocate data-driven solutions that help customers improve clinical outcomes and processes

Design and build scalable production-ready analytics solutions using a wide array of techniques and methodologies in the field of statistical modeling, machine learning, and other AI technologies to meet the needs of given client engagements

Requirements

Minimum of master's degree in Computer Science, Statistics, Engineering, Physics, or other highly quantitative and technically oriented field and 3 years of professional work experience as a quantitative analyst or applied analytics technical leader (healthcare experience preferred)

Mastery of statistical software, scripting languages, and packages- preferred R, Python, SQL

SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of other databases/date-sources.

Solid understanding of supervised and unsupervised ML techniques.

Solid understanding of data structures, software design and architecture.

Ability to work independently and take initiative, but also a co-operative team player.

Proficient at interpreting business questions and applying concepts to data

Excellent Communication and presentation skills, proficiency in data interpretation