Data Scientist

Company:
Location: Remote

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At Liberty Mutual, our purpose is to help people embrace today and confidently pursue tomorrow. That's why we provide an environment focused on openness, inclusion, trust and respect. Here, you'll discover our expansive range of roles, and a workplace where we aim to help turn your passion into a rewarding profession.

Liberty Mutual has proudly been recognized as a “Great Place to Work” by Great Place to Work® US for the past several years. We were also selected as one of the “100 Best Places to Work in IT” on IDG's Insider Pro and Computerworld's 2020 list. For many years running, we have been named by Forbes as one of America's Best Employers for Women and one of America's Best Employers for New Graduates—as well as one of America's Best Employers for Diversity. To learn more about our commitment to diversity and inclusion please visit: https://jobs.libertymutualgroup.com/diversity-inclusion

We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits

Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.

Come join a vibrant data science research team in the emerging field of business lines product pricing and segmentation. A successful applicant is expected to be able to collaborate with business partners to develop predictive analytic solutions that enable data-driven strategic decision-making; and utilize data science techniques to manipulate large structured and unstructured data sets, identify patterns in raw data, and develop models to predict the likelihood of a future outcome and/or to optimize business solutions. This level reflects solid knowledge of predictive analytics techniques, while continuing to learn how to apply techniques to business issues.

Job Responsibilities

  • Apply knowledge of sophisticated analytics techniques to manipulate large structured and unstructured datasets in order to generate insights to inform business decisions.
  • Identify and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business application.
  • Translate quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
  • Enable the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes.
  • Create tools that support product pricing.
  • Be responsible for smaller components of projects of moderate-to-high complexity.
  • Regularly engage with the data science community and participates in cross-functional working groups.

The actual internal level/grade for this role will depend on the candidate's overall experience and skill level. Compensation depends on geographic area.

  • Solid knowledge of predictive analytics techniques and statistical diagnostics of models.
  • Experienced and skilled in programming, preferred in Python.
  • ML/NLP/Deep Learning knowledge/experience is an advantage.
  • Competencies for Analyst II, Data Science typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience, a Master`s degree (scientific field of study) and 2 to 3 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 4+ years of relevant experience.
  • Competencies for Analyst I, Data Science, typically acquired through a Master`s degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience or may be acquired through a Bachelor`s degree and 3+ years of relevant experience.

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