Data Scientist
Dallas, TX, United States
Primary Function:
Upland Capital Group, Inc. is an AM Best rated “A-” VIII specialty property/casualty insurer headquartered in Dallas, Texas. Through its wholly owned insurance carrier, Upland Specialty Insurance Company, the company markets, underwrites and services specialty insurance products in select markets to include excess transportation, construction casualty, excess casualty, primary general liability, excess public entity, professional liability errors and omissions as well as excess cyber liability.
We focus on “old school” underwriting as a craft, add “new school” analytics and technology, and encourage a gritty, growth mindset among people called “we entrepreneurs.”
At our Risk and Analytics (R&A) team, we focus on Actuarial, Data Science, Data and Model Engineering, and Enterprise Risk Management functions. Our Actuarial and Data Science model environment and architecture is containerized, and we are cloud based, running on Azure. Our vision is to build highly automated and efficient processes to build, test, and deploy our models and products for enhancing actuarial, underwriting and claim insights with timely and relevant data-driven analytics and technology. We look to create models that require creative problem solving and a close collaboration with stakeholders across the organization, not limited by a ‘one size fits all’ mindset.
As a startup Excess and Surplus (E&S) carrier, we face unique and interesting problems every day. We are looking for a Data Scientist to join our R&A team. This role will report to the Director, Data Science.
Duties and Responsibilities:
Translate business requirements from different stakeholders into actionable data science projects
Curate modeling datasets using internal and external data sources
Build, test, and deploy models and other analytics products using appropriate techniques
Ensure robust processes are in place for model documentation, monitoring, and maintenance
Research, learn, test, and apply new techniques for non-standard insurance problems
Apply data and model privacy and security protocols with R&A Data and Model Engineering team
Collaborate closely with the rest of the R&A team and other business functions and provide clear and concise communications to the stakeholders
Stay current on industry trends and best practices in data science
Other ad hoc projects such as investigating third party data or enterprise technology solutions
Experience, Education, Special Skills Required:
Bachelor's Degree plus 2 years of Data Science Experience
Required Experience, Education, and skills:
2+ years of technical experience in data science in the insurance industry
Basic understanding of P&C insurance industry
Self-starter, quick learner, and creative problem solver that thrives in a flexible, fast-paced, and remote work environment
Proficiency in programming languages such as Python, R, and SQL
Strong knowledge of a variety of techniques and the ability and interest to learn new techniques quickly (e.g. Regression, Classification, Bayesian, Reinforce Learning, Natural Language Processing, Price Optimization, Large Language Models, etc.)
Preferred Experience, Education, and Skills:
Experience in the end-to-end model creation and deployment process to improve product, pricing, reserving, underwriting, and claims in P&C insurance
P&C insurance domain knowledge, especially knowledge in commercial lines insurance and E&S products
Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Actuarial Science, or related quantitative field
Ability to create production quality code
Experience with non-relational (NoSQL) databases and cloud environment (e.g. Azure, AWS)
Experience with a fully containerized model architecture
Knowledge of agile development practices using Git
Experience with visualization tools such as Power BI
Benefits:
Flexible Time Off
Parental leave
Health Insurance
401k benefits
Dental plans
Vision plans
Life insurance plans
Disability plans
Mental health benefits
Professional development
Education reimbursement
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