Senior Data Scientist

First American Financial Corporation
First American Financial Corporation

Job Overview

Company SummaryJoin our team! As a global leader in providing title insurance, settlement services and risk solutions for real estate transactions, First American (NYSE: FAF) is an ideal place to build your career. We have been entrusted with helping our customers achieve and protect their dream of homeownership since 1889. We believe that our people are the key to the company’s continued success, and we invest in diverse talents and backgrounds and empower our teams to achieve more than they could anywhere else. First American has created an award-winning culture and has been named to the Fortune 100 Best Companies to Work For® list for the fifth consecutive year and to more than 50 regional Best Places to Work lists. For more information, please visit SummarySr. Data ScientistSummary:How would you like to work for one of Fortune’s top 100 Best Places to Work in 2020? At First American, we believe in People First and it shows in the passion and energy of our employees. We are seeking a Sr. Data Scientist to join our growing team.  The ideal candidate will be intricately involved in performing analysis and developing models to support business decisions and manage risk. This individual will work with a variety of data assets from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining and machine learning tasks.  This is a perfect opportunity for the successful candidate to become part of an innovative and energetic team that designs, develops, and implements the most valuable business solutions for the entire organization.Sr. Data ScientistIdentifies business trends and problems through complex data analysis. Interprets results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex machine learning. Designs, develops and implements the most valuable business solutions for the organizationEssential Functions:·         Leverage skills in handling very large datasets to perform exploratory analysis, construct relevant variables, and perform sample design.·         Build complex predictive models to substantially improve business operations.·         Act as technical expert to recommend and develop innovative analytic solutions.·         Communicate and present results to internal audiences, senior leadership, prepare presentations and documentation of models and analytical solutions.Job Complexities:·         Uses skills as a seasoned, experienced professional with a full understanding of industry practices and established policies and procedures·         Troubleshoots a wide variety of complex problems and identifies solutions within broad applications and functional expertise·         Regularly provides input to define and implement conceptual issuesKnowledge and Skills:·         Extensive experience with large datasets·         Knowledge and experience with diverse statistical and machine learning methods (e.g. – GLM/Regression, Decision Trees, Clustering, PCA, SVM, Classification, Ensemble methods etc.)·         Demonstrated proficiency with machine learning languages such as Python or R·         Understanding of RDBs and interactive SQL programming skills·         Aptitude for picking up new technologies·         Excellent verbal and written communication skillsEducation:·         BS or equivalent in Mathematics, Statistics, or Computer Science·         MS or PhD degree preferredTypical Range of Experience:·         5-7 years’ experience building predictive and descriptive machine learning modelsFirst American invests in its employees’ development and well-being, empowers them to provide superior customer service and encourages them to serve the communities where they live and work. First American is committed to diversity and inclusion. We are an equal opportunity employer. For more information about our Company and our dedication to putting People First, check out time

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