• Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.
• Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business application.
• Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
• Enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes. Customizes analytic solutions to specific client needs.
• Responsible for smaller components of projects of moderate-to-high complexity.
• Regularly engages with the data science community and participates in cross-functional working groups.

Qualifications

• Solid knowledge of predictive analytics techniques and statistical diagnostics of models. Foundational/intermediate knowledge of predictive toolset; expert resource for tool development.
• Data extraction and manipulation skills, EDA, transformations, comfort manipulating and analyzing high-volume, high-dimensionality data from varying sources, both structured and unstructured. Preferred skills developing algorithms and products with clustering (KNN), generalized linear models (GLM), Random Forest, XGBoost, time series (ARIMA), NLP, Process and Pattern Mining using popular ML frameworks, Python (Pandas, Numpy, scikit-learn, PyTorch), SQL, Spark, TensorFlow, project versioning in git, and MLflow model deployment.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely - strong customer focus, ownership, urgency and drive.
• Effective analytical, troubleshooting and problem-solving skills - has a value-driven perspective with regard to understanding of work context and impact.
• Competencies 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.

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.