Senior Data Scientist, Asset Protection & Risk Management

Overview

REI Co-op is united in finding better ways to work. The goal is to help people find and enjoy the outdoors. When you work for the co‑op, you do your best work. You also get support to live your best life. You help shape the future of the outdoors for people and the planet.

As the Asset Protection & Risk Management Sr. Data Scientist at REI, you will work with cross‑functional data sets. You will influence the long‑term growth of our department’s analytics capability. You should have exceptional technical, business, and communication skills. You must translate key business questions into data processes, data sets, models, and examination that answer those questions.

You will drive regular deep, topical analyses of strategic and tactical questions focusing on an industry concept of Total Retail Loss. You will also help create and maintain all data pipelines and analytics strategy for the Asset Protection and Risk Management team. This role uses knowledge of statistical modeling, technical skills, and business understanding to build insights and capacity. This helps REI deliver exceptional results.

The ideal candidate is a self‑starter with many technical and critical skills. The candidate should be skilled at turning data findings into clear, useful insights.

• Show an infectious curiosity and exceptional determination. Have a deep commitment to learning and applying knowledge to solve important business problems. Push the boundaries of our abilities.
• Thrive in an environment of change and uncertainty. Apply scientific objectivity and intelligent ingenuity to solve problems and test hypotheses and beliefs.
• Proactively develop new metrics and studies to quantify the value of different aspects of business processes and consumer behavior
• Translate analytic insights into concrete, actionable recommendations for business or product improvement
• Highly skilled at querying relational databases (SQL). Able to automate and maintain processes to pull and integrate data from many different sources.
• Translate and effectively communicate future business needs into requirements that inform enterprise analytics platform strategy
• Integration of internally and externally produced unstructured, semi‑structured, and relational data sources
• Build and maintain processes to acquire, transform, and curate multiple types of data necessary for examination and insights
• Possess exceptional writing, data visualization, and communication skills. Can explain complex quantitative examination clearly and precisely to senior executives.
• Have a solid passion for answering hard questions with data. Demonstrate the ability to create and implement new ideas at many levels of the organization.
• Revel in the complex, but seek to simplify and clarify in your examination and communications
• May perform other ancillary duties including but not limited to: coordination of testing, tuning, troubleshooting, business consultation and training

• Bachelor’s degree in computer science, computer engineering, mathematics, statistics, physics, or other quantitative discipline required
• 5+ years of related work experience as a data scientist, predictive analyst, statistician, quantitative analyst or actuary.
• Demonstrated ability to self‑educate and learn while doing in a highly complex, ambiguous, and rapidly changing environment.
• Exceptional experience in developing sound analytics‑based solutions to business problems
• Proficiency in at least one modern programming language and a statistical programming language, Python & R preferred
• Has deep experience with SQL and relational data models. Has exceptional skills in visualization tools like Tableau and Sigma. Has exceptional skills in Microsoft tools like Excel and VBA.
• Excellence in applying critical rigor & technical proficiency to the business environment
• Demonstrate skill in explaining complex technical and critical ideas to non‑technical audiences. Adjust communication style to fit the audience at any level of the organization.

• Master’s Degree or Ph.D.
• Hadoop knowledge/Experience, Map Reduce, HBASE/HIVE, Basic Spark
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