Data Scientist - Model Validation (REMOTE)

Key Skills

Java Programming, Finance, Python Programming, SQL, AWS, Data science techniques, R Programming, Linux Operating system, SAS

Job Description

We offer competitive benefits and pay with the potential for an annual financial award based on both individual and enterprise performance. Our employees have an opportunity to participate in volunteer events within the community and engage in a learning culture. We offer programs to assist with tuition reimbursement, professional designations, employee development, wellness initiatives, and more!

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Responsibilities

Model Validation at State Farm:

In this role you will be responsible for the independent review and validation of various types of models, including machine learning models that are being developed or have been implemented at State Farm. Statistical areas of model review include but are not limited to: problem design, data engineering, model development, and model documentation including plans for implementation, monitoring, and performance validation. Furthermore, you will rely on your experience to discuss alternative approaches as well as develop alternative models to the ones proposed by other data scientists. Moreover, the Model Validation team provides periodic independent statistical consultation, analysis, or modeling work apart from independent review.

Why Join Our Team:

Implementing solutions is critical for success for data science at State Farm. As part of the Model Validation team, your role will consist of problem identification, solution proposals and presentations to a wide variety of management & technical audiences. This role allows you the to work on multiple concurrent projects in a community setting, develop yourself and others, and advance data science both at State Farm and externally. The variety of projects, technologies, and statistical techniques will create an unbounded development opportunity for enhancing your analytic skills.

Qualifications

Competitive candidates will bring:

• Completed Masters, other advanced degrees, and 3+ years of experience in an analytical field such as data science, quantitative marketing, statistics, operations research, management science, industrial engineering, economics, etc.
• 5+ years of experience building predictive models preferred. 
• Experience engaging in quantitative analysis on many non-standard and unique business problems. Candidates with experience conducting analysis in the Insurance or Financial industry preferred. 
• Experience with data cleansing, feature creation, feature selection and value imputation.
• Experience with Python, R, and/or SAS
• Experience with cloud-based environments (e.g.,AWS) and/or Linux
• Thorough understanding of generalized linear models
• Knowledge of at least two (2) of the following methods:
• time series analysis
• cluster analysis
• tree-based algorithms, or
• neural networks