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The Enterprise Data Scientist I will be a valuable part of the Data Science team who provide statistical analysis, modeling, and vis ualization services for all lines of business and all shared service functions at Farmers Insurance Group. The Data Scientist 1 will work on end to end solutions as part of a team. They will design innovative analytic models and will be responsible for pulling and cleaning datasets, evaluating models, and presenting results to internal teams.
Essential Job Functions
Extract data from a variety of sources (databases, web, text files) and in a variety of formats (structured, unstructured, JSON, Parquet, etc.) and prepare the data for analysis Describe data using qualitative and quantitative aggregation/summarization and build tools (static reports, interactive dashboards, web applications) that allow clients to easily view and understand important patterns and trends in the data Provide quantitative comparisons of data points using advanced statistical analysis including data reduction techniques (PCA, cluste ring), resampling (permutation tests, Monte Carlo testing) as well as traditional statistical hypothesis testing Construct and validate predictive models using a variety of techniques
Master's degree in scientific or quantitative field and documented academic excellence. PhD in scientific field preferred
At least year in a data analytics role (business intelligence analyst, data analyst, etc.)
Special Skill Requirement
Proficiency in at least one of the following is absolutely required: R, Python Basic proficiency in at least one of the following: PowerBI, Tableau, QlikView, D3.js Basic proficiency in SQL Able to implement and utilize advanced statistical and machine learning techniques (GLMs, PCA, cluster analyses, ARIMA, ETS, decision trees, SVM, neural networks, ensemble methods, etc.) Basic familiarity with project management tools (Asana, Basecamp, LiquidPlanner)
Farmers is an equal opportunity employer, committed to the strength of a diverse workforce. ]]>
Job Posting: 04/22/2019