Data Scientist | GEICO | Chevy Chase | Maryland | Job Alert | Latest Jobs 2021


Data Scientist | GEICO | Chevy Chase | Maryland | Job Alert | Latest Jobs 2021

About Company

Working out of our Chevy Chase, MD/Washington DC office, GEICO’s Data Science team uses predictive analytics and innovative machine learning models to make value from data. We solve problems across GEICO, from Marketing to Claims and Underwriting, and are liable for developing and driving strategic modeling initiatives.

We see our projects through the whole data science lifecycle, from problem definition to data exploration, data munging, modeling, analysis, and deployment into production systems. We maintain an in depth partnership with IT to make sure that our models are often deployed quickly and monitored during a flexible deployment framework.

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Job Description

As Data Scientist, you’ll be a member of this diverse and highly skilled team. On any given day, you’ll be exploring new data sets with a business or IT partner, learning the intricacies of a business process, building models, or coordinating the productionalization of a model. you’ll use a spread of tools (including SQL, Python, R, Spark, and shell scripting) during a sort of environments (including various databases, Linux servers, and Hadoop). You’ll add a highly collaborative, team environment where you’ll quickly develop wide ranging exposure to new methods and best practices for conducting data science during a commercial environment.

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  • Bachelor’s degree in a quantitative discipline, such as statistics, data science, computer science, mathematics, engineering, physics, etc. Advanced degree strongly preferred
  • 2+ years’ experience and solid understanding of machine learning techniques. Academic and internship experience may also be considered.
  • 2+ years’ experience of combined industry/academic experience with predictive modeling, and advanced analytics
  • Solid understanding and experience with advanced statistics and modern machine learning predictive techniques such as GLMs, decision trees, forests, boosted ensembles, neural networks, deep learning, etc.
  • Strong coding skills using common data science tools, such as Python (strongly preferred), R, Linux/Unix command line and shell scripting, etc. 
  • Strong skills in data processing using SQL, Hive, Impala, Spark, or equivalent querying language
  • Familiarity with distributed storage and big data computing technology (AWS, Hadoop, Spark, etc.)
  • Excellent communication skills
  • Passion for extracting hidden insights and building machine learning systems that enhance business outcomes

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