Overview

If you love the outdoors, skiing, and/or hiking we have a position for you. Our client in Bend, Oregon is looking for a Senior Data Scientist. They have a collaborative work environment where team members are empowered to “run with” ideas to improve processes.

Responsibilities

This person will be responsible for Conduct data science, Contribute to Data Science and BI Team effectiveness, and Contribute to BI Portfolio effectiveness. You will play a key role in transforming structured and unstructured data into insights and models for business decision-making.

The Data Scientist performs individual work assignments, participates in working groups and contributes to enterprise projects, often independently representing the Data Science and BI Team. You’ll bring strong business acumen and the ability to frame business problems and transform them into analytical problems to be solved using appropriate data science methods.

Qualifications

Degree in applied mathematics, statistics, computer science, operations research, or a related quantitative field or Hands-on Experience accepted in lieu of.

3-6 years of experience in executing data science projects, preferably in the domains of customer behavior prediction and operations management.

Advanced coding knowledge and experience in at least two programming languages: for example, R, Python/Jupyter, C/C++, Java or Scala.

Advanced knowledge of database programming languages including SQL, PL/SQL, or others for relational databases, graph databases or NoSQL/Hadoop-oriented databases.

Broad Knowledge and experience in statistical and data mining techniques that include a generalized linear model (GLM) / regression, random forest, boosting, trees, text mining, hierarchical clustering, neural networks, graph analysis, data sampling, design of experiments, etc.

Familiarity with typical algorithms used by retail businesses (i.e., Churn, Segmentation) required.

Technical skills for working across multiple deployment environments including cloud, on-premises, and hybrid and skills for acquiring new datasets, parsing datasets, organizing datasets, representing data visually and automating data-driven models.

Advanced knowledge of statistical tools and advanced analytics platforms such as Minitab, SAS, Knime, Dataiku, Anaconda, Google Collaboratory

Certified Analytics Professional credential (available through INFORMS.ORG)

Preferred

Masters Degree in applied mathematics, statistics, computer science, operations research, or a related quantitative field