Senior Data Scientist

Location: Los Angeles, CA
Date Posted: 01-15-2018
Remote Work Opportunity

Our client works with major health insurers to resolve the problems associated with the high-cost of untreated health conditions. They rely heavily upon applied predictive analytics to identify and engage care-avoidance individuals through their proprietary and proven methodology.
ITStaff has been engaged to help our client find a senior data scientist for their team that is open to working in the fast-paced environment of a rapidly growing company. The ideal candidate should be a self-starter who is comfortable making appropriate modeling decisions aligned to strategic business goals.
What You'll Be Doing

As a data scientist, you will run, develop, and use analysis tools for data integration and organization and run analytical experiments and evaluate models to help our client service the healthcare industry. You will analyze processes and systems to extract insights from structured and unstructured data and be a thought-leader, seamlessly combining proven business acumen with deep technical skills.  You will also be assisting in the design, development and implementation of valuable business solutions by preparing and cleaning data, designing and coding decision support systems and measuring their performance using advanced decision science. Responsibilities also include interpreting data from multiple sources using a variety of statistical and machine learning techniques to provide guidance to the business and identify markets that would benefit from our client’s services. 

  • Bachelor's degree in Mathematics, Engineering, Business, Data Science, Economics, Physics or related field of study (Master’s Degree is strongly desired)
  • Strong knowledge of statistical modeling and machine learning techniques such as logistic regression, neural networks, survival analysis, Bayesian networks, Naïve Bayes nets, linear regression, random forest, decision/regression trees, random forests, time series analysis, SVM, LASSO, ridge regression, ensemble methods, and genetic algorithms
  • Experience in quantitative analytics
  • Experienced developing in Python or SQL
  • Experience using R, Hadoop, Pig, Hive, or Spark is desired
  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate information with attention to detail and accuracy 
  • Demonstrated experience with database design, data models, and integration/extraction technologies, statistical modeling, and machine learning
  • Excellent verbal and written communication skills
  • Able to multitask, prioritize, and manage time effectively
  • Creative problem solver who thrives when presented with a challenge
  • Encouraging to team and staff; able to mentor and lead.  Goal-orientated.
  • Up-to-date on latest industry trends; able to articulate trends and potential clearly and confidently
  • Able to work in a fast-paced environment
  • A history of working with medical claims data is a plus, but not a requirement

  • Gathering, cleaning, managing, and maintaining high quality data
  • Designing features from rich data available from many sources
  • Exploring analyses to identify and interpret trends, patterns, and relationships in complex data sets using advanced tools and models 
  • Formulating machine learning approaches while paying attention to metrics
  • Training, evaluating, and deploying models
  • Anomaly detection and other diagnostics
  • Graphical model analysis and data visualization
  • Identifying key prediction/classification problems, devising solutions and building prototypes
  • Conducting statistical analyses to support business strategies
  • Staying current on published statistical/machine learning techniques and technologies and sharing these findings with other data scientists in the organization
  • Participating in software-focused marketing efforts
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