Predictive Analyst - Telematics

Location US-OH-Richfield
Posted Date 9 months ago(12/27/2019 1:12 PM)
Job ID
# of Positions
National Interstate
Position Type
Full Time


National Interstate is a member of Great American Insurance Group. As one of the leading commercial transportation insurers in the nation, we offer risk financing solutions in all 50 states tailored to meet the needs of a wide variety of transportation classes. Our offerings include traditional insurance and innovative alternative risk transfer (ART) programs, including more than a dozen group captive programs catering to niche wheels markets. We are proud to be a multiple Northcoast 99 winner and Cleveland Plain Dealer Top Workplace in Northeast Ohio. It is because of our talented and dedicated team that we are able to live out our company values of integrity, transparency, fairness, accountability, empowerment and collaboration with each transaction we make. If you are ready to join an engaging and driven team such as ours, we would love to hear from you!


Seeking a senior analyst for our telematics team to help optimize risk management services and underwriting solutions for our customers. In this role, you’ll work with aggregated telematics data in order to determine risky driving behavior, running these results through a series of algorithms to create our solutions which integrate into all aspects of NATL’s value chain. This role will be heavily involved with data acquisition, processing, and application of machine learning models, as well as pulling data from both new and familiar sources to quickly evaluate its efficacy.  Furthermore, the candidate will need the ability to learn new tools on the fly and be adaptable to changing requirements.


What you'll do:

Product Analytics

  • Technical SME for telematics data.
  • Lead discussions with client stakeholders to understand business problems and formulate solutions
  • Will work with IT acting in business analyst capacity to interpret product, claims and risk management requirements. Help prioritize the feature implementation pipeline
  • Interpret data, analyze results using statistical techniques and provide ongoing insight, internally to business development leaders, externally to customers
  • Telematics consultative services to internal (NATL) customers and in , including identifying and helping to resolve exposures with significant loss potential, investigating cause/effect of major losses and evaluating safety management programs.

Product Modeling

  • Lead data collection, wrangling and visualization efforts by maintaining high level of data integrity and accuracy.
  • Conduct formal statistical analyses using R or relevant tools to interpret diagnostics information on telematics
  • Work with PDM, OM and DA to whiteboard Telematics use cases and provide model based support for hypothesis testing
  • Provide recommendations on implementing significant variables to existing product models – approach, implementation plan and release schema
  • Lead discussions with technology, data-warehousing, other internal teams to resolve issues, deploy the models etc.
  • Identifying, evaluating, and productionizing new data sources (e.g. geospatial data, web scraping, location services)
  • Building anomaly detection models to determine unexpected trends in data, issues with data quality, etc.


  • 4+ years industry experience building predictive models in statistics, physical sciences, engineering, or other technical disciplines OR graduate-level research in relevant fields
  • Strong programming skills (preference of Python OR R)
  • Experience with query languages and SQL databases and/or NoSQL database’s such as MongoDB, Cassandra, HBase.
  • Demonstrated experience in building, validating, and leveraging machine learning models
  • Demonstrated skill with data mining, data munging, coping with missing/corrupt/ unstructured data
  • Experience with at least some of the following: geospatial data tools, web scraping, merging with large external data sources
  • Preferred: Experience handling Restful APIs calls using appropriate tools, JSON/ XML schema using relevant programming tools, big data tools (e.g. Hadoop, Spark) and cloud computing, version control system (TFS preferred) and building insurance pricing models



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