Director, Data Science

Primary Function: 

UplandCapital Group, Inc. is an AM Best rated “A-” VIII specialty property/casualtyinsurer headquartered in Dallas, Texas. Through its wholly owned insurancecarrier, Upland Specialty Insurance Company, the company markets, underwritesand services specialty insurance products in select markets to include excesstransportation, construction casualty, excess casualty, primary generalliability, excess public entity, professional liability errors and omissions aswell as excess cyber liability.  

 Wefocus on “old school” underwriting as a craft, add “new school” analytics andtechnology, and encourage a gritty, growth mindset among people called “weentrepreneurs.” 

 Atour Risk and Analytics (R&A) team, we focus on Actuarial, Data Science, Dataand Model Engineering, and Enterprise Risk Management functions. Our Actuarialand Data Science model environment and architecture is containerized, and weare cloud based, running on Azure. Our vision is to build highly automated andefficient processes to build, test, and deploy our models and products forenhancing actuarial, underwriting and claim insights with timely and relevantdata-driven analytics and technology. We look to create models that requirecreative problem solving and a close collaboration with stakeholders across theorganization, not limited by a ‘one size fits all’ mindset. 

Duties and Responsibilities:

• Lead and manage a team of data scientists through the end-to-end data science solution development process: 
• 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 
• Manage and develop the data science team 
• Create and promote an open, learning, and collaborative culture 
• Ensure the team works together to deliver high quality projects on a timely basis, and identify risks and dependencies to the project deliverables 
• Provide guidance and mentorship to the junior data scientists, fostering their professional growth 
• Serve as a subject matter expert and a stakeholder in Upland's data, analytics, and technology strategies 
• 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 

Required Experience, Education, and Skills:

• 5 years of technical experience in data science in the insurance industry 

• Strong P&C insurance domain knowledge 

• Strong leadership qualities through direct or indirect people and project management 

• 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 

• Experience 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 
• Credential P&C modeling specialist or actuary (e.g. ACAS, FCAS, or CSPA) 
• Experience in people management 
• 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