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Homeoffice Data Scientist

Dice  ·  United States, Vereinigten Staaten Von Amerika · Remote

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About the job

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Blue Ocean Ventures, is seeking the following. Apply via Dice today!

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.

Experience: -

  • Minimum 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
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