The legal world is in the midst of a Data Science and AI revolution. The Liberty Mutual Legal department is at the forefront of the legal transformation applying advanced data science tools such as deep learning and NLP to legal problems.
We are looking for a talented data scientist to join our team building AI and decision support tools that help our clients and policyholders obtain better outcomes on legal related issues.
In this role, you will collaborate closely with a team of data scientists, analysts, and IT developers. You and the team will work with clients across the company to develop strong understanding of business needs. You will research and apply machine learning and statistical algorithms to projects aimed at revealing the drivers of legal cost and related outcomes.
Example projects include using deep learning based NLP models classify millions of text-based legal records, machine learning models to predict the outcome of a case, and using Bayesian hierarchical models to estimate causal effect of legal decisions.
- Develop predictive and explanatory models that help improve legal decision making
- Develop models and analysis on unstructured text using deep learning and other NLP (Natural Language Processing) techniques
- Perform all data preparation and exploratory data analysis steps
- Guide implementation, testing, and evaluation of models.
- Work with clients to develop strong understanding of business needs and use business understanding to help design effective analytical solutions
- Manage and execute all aspects of analytic initiatives, including developing project plans and guiding other team members
- Present methodology and results of analysis to a broad range of audiences, including both technical and non-technical, at all levels of the organization
- Collaborate closely with other members of the Legal Analytics and Data Science team and the Liberty Mutual Data Science community
The actual internal level/grade for this role will depend on the candidate’s overall experience and skill level.
- Bachelor’s degree in Statistics, Economics, Computer Science, or any quantitative discipline with relevant work experience, required; advanced degree a definite plus
- Significant professional experience required applying quantitative analysis and modeling to solving real-world business problems including experience in model validation, testing and deployment
- Adept at framing business questions and practices in analytic terms, and translating business requirements into corresponding datasets, analyses, models, and reports
- Experience communicating technical results to both technical and non-technical users using effective story telling techniques and visualizations
- Demonstrated ability to perform high quality work both independently and collaboratively as a project team member or leader
- Demonstrated proficiency in R or Python required
- Experience applying Deep Learning and/or NLP techniques (especially using Tensorflow or PyTorch) on large unstructured data highly preferred
We value your hard work, integrity and commitment to positive change. In return for your service, it’s our privilege to offer you benefits and rewards that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits
At Liberty Mutual, we give motivated, accomplished professionals the opportunity to help us redefine what insurance means; to work for a global leader with a deep sense of humanity and a focus on improving and protecting everyday lives. We create an inspired, collaborative environment, where people can take ownership of their work; push breakthrough ideas; and feel confident that their contributions will be valued and their growth championed.
We’re dedicated to doing the right thing for our employees, because we know that their fulfillment and success leads us to great places. Life. Happiness. Innovation. Impact. Advancement. Whatever their pursuit, talented people find their path at Liberty Mutual.
- Project Management
- Information Technology
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1