Senior Data Scientist in Portland, OR

$80K - $100K(Ladders Estimates)

Cambia Health Solutions   •  

Portland, OR 97201

Industry: Healthcare

  •  

Less than 5 years

Posted 42 days ago

Overview

Senior Data Scientist

Seattle, WA or Portland, OR

Responsibilities & Requirements

Cambia Health Solutions is working to create a seamless and frictionless health care experience for consumers nationwide. This presents a unique challenge and opportunity for innovative and disruptive solutions from the Data Office.

Our Data Scientists design, develop, and implement data-driven solutions using machine learning technologies and advanced statistical analyses. You should be passionate about finding insights in data, comfortable withlarge and fragmented data sets, and command a variety of analytic tools at your disposal.

In addition to quantitative mastery, the ideal candidate will effectively interpret and communicate strategic results to varied audiences, and provide analytic support for companywide process and operational improvement efforts. The ideal candidate is an independent, solution-oriented thinker witha strong background processing large data sets, applying analytical rigor and statistical methods, and driving toward actionable insights and novel solutions.

Minimum Requirements

  • The Senior Data Scientist would have a Masters or PhD degree in a strongly quantitative field such as: Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, or Econometrics, and 8years of database analytics experience or equivalent combination of education and experience. PhDdegree preferred.
  • BA/BS degree (or equivalent experience) in a strongly quantitative field such as: Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, or Econometrics and 3 years of related work experience or equivalent combination of education and experience. Master's or PhD degreepreferred.
  • Whole-brain thinking: Possessing the ability to think creatively and demonstrate analytical skills, analyzing complex situations both alone and as part of a team, learning quickly and synthesizing solutions, options and action plans.
  • Familiarity with mixed methods research, experience with at least two of the below:
  • Understanding of advanced analytics (e.g., statistics, simulation, optimization) and methods such as time series analysis, longitudinal studies, and life event modeling.
  • Demonstrable knowledge of, and practical experience applying, data mining methodologies, natural language processing, and machine learning algorithms (e.g. regression, clustering, neural networks, kernel methods, dimensionality reduction, ensemble methods, decision tree methods).
  • Experience with tools for data mining, statistics, analysis, and scripting (e.g., R, SAS, Scala, MATLAB, Python, Ruby).
  • Experience with cleaning, aggregating, and pre-processing data from varied sources. Experience creating complex SQL queries for standard as well as ad hoc data mining purposes.
  • Demonstrated ability to analyze and interpret qualitative data (research, feedback) and incorporate such insights into quantitative analyses.
  • Practical ability to visualize data and analytical results, and excellent communication skills to effectively collaborate and communicate with a broad array of internal and external contacts.
  • Strong facilitation skills, including the ability to resolve issues and build consensus among groups of diverse stakeholders.
  • Demonstrated ability to apply quantitative analysis techniques to business situations including forecasting, descriptive statistics, statistical inference, and multivariate modeling techniques.
  • Demonstrated ability to create complex SQL queries, analyze large amounts of data, interpret qualitative data (research, feedback) and incorporate into analyses.
  • Excellent oral and written communication skills to effectively interface and communicate with a broad array of internal and external contacts including leadership.
  • Proficient with a range of business intelligence and analysis tools SAS, Business Objects, SQL Server Reporting Services, SPSS, Minitab, R, Microstrategy, or Tableau.
  • Experience with at least one statistical/analytical programming tool (SAS, R, Python, Stata, MATLAB, etc).
  • Coursework or practical experience with machine learning, data mining, and constructing analytical models and algorithms.
  • Demonstrated ability to work with minimal direction, with the ability to coordinate complex activities.
  • Strong understanding of and experience with mixed methodologies below:
  • Experience with advanced analytics (e.g., statistics, simulation, optimization) and methods such as time series analysis, longitudinal studies, and life event modeling.
  • Detailed knowledge of, and practical experience applying, data mining methodologies, natural language processing, and machine learning algorithms (e.g. regression, clustering, neural networks, kernel methods, dimensionality reduction, ensemble methods, decision tree methods).
  • Experience with tools for data mining, statistics, analysis, and scripting (e.g., R, SAS, Scala, MATLAB, Python, Ruby).
  • Experience with cleaning, aggregating, and pre-processing data from varied sources. Experience creating complex SQL queries for standard as well as ad hoc data mining purposes.
  • Demonstrated ability to analyze and interpret qualitative data (research, feedback) and incorporate such insights into quantitative analyses.
  • Familiarity with retail, e-commerce, or financial analytics, including approaches such as life event modeling, customer lifetime value.
  • Experience in Hadoop, Spark, Storm or related paradigms and associated languages such as Pig, Hive, Mahout. Demonstrated experience programming (e.g. Java/C++, Scala, R, Python, Julia).
  • Familiarity with Agile/SCRUM methodologies.
  • Experience with a range of business intelligence and analysis tools (such as SAS, Business Objects, SQL Server Reporting Services, SPSS, Minitab, R, Microstrategy, or Tableau).
  • Demonstrated experience operating in a Unix/Linux environment, or Hadoop environment.
  • Demonstrated understanding of research and ability to develop methodologies in data mining and other innovative statistical/mathematical approaches.
  • Demonstrated high level technical and analytical skills, with the ability to analyze complex situations, learn quickly and synthesize corresponding solutions, options and action plans.
  • Demonstrated understanding of the principles of rigorous experiment design and analysis.

Data Scientist Senior would have a Masters or PhD degree in a strongly quantitative field such as: Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, or Econometrics, and 8 years of database analytics experience or equivalent combination of education and experience. PhD degree preferred.

Valid Through: 2019-10-29