Liberty Mutual is looking to leverage advanced analytics and machine learning techniques, particularly in Natural Language Processing (NLP) and Computer Vision, to generate insights, inform business decisions, support risk selection and pricing, and develop predictive models for insurance applications.
Requirements
- Demonstrated knowledge with deep learning modeling and programming including PyTorch and Tensorflow.
- Predictive modeling, data science techniques, machine learning models and statistical methods.
- Deep Learning techniques including deep neural networks (DNN) and their applications.
- Python and R programming through hands-on experience.
- Computer Vision modeling expertise.
- Demonstrated advanced knowledge of Natural Language Processing including CNN, RNN, LSTM, Transformers and Large language models.
- Machine Learning expertise in building models including GLM’s, Logistic Regression, Tweedie regression and XGBoost.
Responsibilities
- Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.
- Designs, develops and deploys Natural Language Processing (NLP) models and algorithms such as transformers, encoder and decoder models in projects.
- Explores and applies Computer vision algorithms in insurance domain.
- Applies machine learning models to support risk selection and pricing decisions in insurance.
- 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.
- Documents and presents work progress, findings, and potential chances to both technical and non-technical audience.
Other
- Telecommuting permitted up to 100%.
- Employer will accept a Ph.D. degree (or foreign equivalent) in a Mathematics, Statistics, Physics or a related field and two (2) years of experience in the job offered or in an Assistant Director, Data Science -related occupation.
- Regularly engages with the data science community and participates in cross-functional working groups.
- Guide others as a technical consultant for the team.
- Customizes analytic solutions to specific client needs.
