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Analytics Consultant
CNA Financial Corporation
Chicago, IL, United States
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Description
Job Summary
The successful candidate will use statistics and machine learning to build and refine state-of-the-art predictive models for the pricing, underwriting, administration, and marketing of an exciting mix of commercial insurance products, ranging from Surety to Professional Liability to more traditional lines like Workers Compensation. These models support key personnel such as underwriters and claims adjusters in tactical decision-making and also are used by senior management in formulating strategy.
Essential Duties & Responsibilities
1. Builds and validates predictive models in collaboration with business partners in functional areas such as Underwriting, Pricing, Distribution, Claims, Risk Control, and IT.
2. Designs, writes, and tests computer programs to extract and analyze data, to build models, and to support implementation.
3. Interprets the results of models in business terms and communicates the contents of the models to business decision-makers.
4. Participates in crafting products and innovative solutions that will provide revolutionary change.
5. Participates in special projects requiring quantitative expertise.
Reporting Relationship
AVP or above
Skills, Knowledge & Abilities
Required:
• Demonstrated technical excellence in statistics and data science
• Proficiency with SQL and with standard statistical software (e.g., R)
• Proficiency with classical statistical models such as logistic regression and other GLMs.
• Strong analytical and problem solving skills
• Attention to detail and accuracy of work
• Strong interpersonal and communication skills
• Strong writing skills, including writing coherent documentation and reports
• Ability to work collaboratively in a team environment
• Strong time management skills and a sense of urgency
• Drive to continuously improve
• Drive to focus on meaningful deliverables that impact the bottom line
• Ability to work effectively with colleagues with diverse perspectives and backgrounds
Preferred:
• Practical experience with distributed computing (e.g., Spark)
• Practical experience with Python
• Experience utilizing machine learning techniques (e.g., random forests) and deep learning
• Knowledge of the core functions of an insurance company
• Product specific commercial and/or specialty insurance knowledge
• Knowledge of Microsoft Office Suite and other business related software
Education & Experience
1. Bachelor's Degree in a relevant discipline, or equivalent.
2. Typically a minimum of four years of related work experience.