Analyst II, Data Science
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Are you looking for a position where you can work in a team at the cutting edge of insurance pricing research and discover deep relationships between driving behavior and risk? Where you can work with billions of miles of telematics data to aid in the development of new products and help make the roads a safer place? Our Global Retail Markets Product Design and Modeling department is seeking a talented data scientist to develop pricing models and lead research projects for our Usage Based Insurance (UBI) products: from understanding the data captured to producing pricing for new and existing products. This highly technical position will be a great fit for someone who is passionate about discovering new knowledge and developing solutions at the frontier of a constantly evolving market space!
The successful candidate will have a proven track record of working effectively with highly talented professionals to develop creative solutions to complex problems, be comfortable with data and modeling, and understand the business goals and strategy. Solid communication and interpersonal skills are critical to the role, and the individual we hire will work very closely with their team, internal partners and external vendors as we work to test and implement new ideas. This is a visible position in a quickly growing area, where you will have a key role in expanding the UBI pricing capabilities of the organization worldwide.
- Build pricing models and novel features for Liberty Mutual's UBI programs
- Explore and utilize advanced modeling techniques to inform pricing decisions
- Translates quantitative analyses and findings into solutions to business problems
- Understands clear trade-offs between and among choices, with a reasonable view into likely outcomes
- Partner with internal and external teams to develop UBI product design and research projects
- Collaborate with internal stakeholders to help develop novel UBI research applications
- Potential to work with massive amounts of raw telematics sensor data to build sophisticated models describing automobile driver behavior
- Regularly engages with the data science community and leads cross functional working groups
- Bachelors w/ 4+ years, Masters w/ 2+ years, or Ph. D with 0-1 years of relevant experience in a quantitative field
- Demonstrated ability to exchange ideas and convey complex information clearly and concisely, both verbally and in writing
- Experience with predictive modeling and statistical software packages (e.g., SAS, Emblem, Python/R)
- Strong programming skills, especially Python, R and SQL
- Experience with Spark, Hadoop, AWS EMR, Presto or other common big data tools is preferred
- Experience using a version control system such as Git
- Experience with popular machine learning and deep learning frameworks (e.g. H2O, TensorFlow, PyTorch, SparkML, MXNet) a plus
- Prior experience with high-frequency data and signal processing a plus