Headquartered in the heart of downtown Chicago, CNA is a leading commercial and specialty insurer, offering a diverse range of insurance products including Workers Compensation, Property, General Liability, Professional Liability, Cyber Insurance, Surety, and Warranty. We are one of the world leaders in underwriting non-medical professionals, from lawyers and accountants to architects and management consultants.
What CNA offers
• A collaborative data science team with diverse skills and experiences, combined with deep expertise in statistical modeling, machine learning, and applications to insurance
• Modern cloud computing environment that enables you to explore data and new tools, build and deploy sophisticated models that impact key areas such as underwriting, pricing, claims management and risk control
• Sponsorship of continued professional growth through support for attending technical conferences, meetings and symposia
The successful candidate will:
- Research and implement novel statistical, machine learning approaches to address complex business questions in order to advance our approach to data science.
- Implement, maintain and document internal proprietary data science libraries to facilitate efficient and reusable processes.
- Dive into new methods and technologies and embrace the ambiguity of research problem solving.
- Use statistical methodologies and machine learning techniques to build state-of-the-art predictive models to solve business problems across CNA.
Essential Duties & Responsibilities
- Develop a deep understanding of the underpinnings of advanced algorithms while using their own expertise to create new solutions for business problems across CNA
- Update and improve existing data science proprietary tools to incorporate new features
- Implement creative quantitative solutions into high quality, reusable and well documented code libraries
- Collaborate with Technology to rapidly prototype algorithms and code for proof-of-concept demonstrations to advance our cloud analytical capabilities.
- Communicate research findings and solutions in a clear manner and participate in training other data scientists in using the newly developed tools
- Collaborate closely with team members to advance the data science capabilities at CNA and contribute to the team’s intellectual capital
- Champion the use of data science to drive change and to provide superior decision support
- Participate in special data science projects requiring advanced quantitative expertise and interpret the results of algorithms to business decision-makers
Required Skills, Knowledge & Abilities
- Proven experience in coming up with creative analytical approaches demonstrated through impactful business solutions or academic publications
- Advanced knowledge of R and /or Python demonstrated through advanced statistical/ ML algorithms implementation and library development
- Deep expertise in applying statistical and machine learning methods to solve complex problems using structured and unstructured data
- Practical experience with version control tools such as git
- Intellectual curiosity and drive to continuously learn new tools and methods
- Strong analytical, problem solving and critical thinking skills
- Attention to detail and accuracy of work, ability to spot and correct issues
- Strong writing skills, including writing coherent documentation and reports
- Strong interpersonal and communication skills
- Ability to interpret algorithm results and communicate insights to technical and non-technical audiences
- Ability to work collaboratively with colleagues with diverse perspectives and backgrounds
- Strong time management skills
- Capable of operating with little supervision and thinking independently and innovatively
Preferred Skills, Knowledge & Abilities
- Experience with applying deep learning methods to natural language processing problems
- Experience with using C++ for advanced algorithm implementation
- Experience with Machine Learning Model Interpretation methods
- Experience in working with data and tools to design processes in a cloud environment, preferably Google Cloud Platform
Director or above
Education & Experience
Advanced degree in a quantitative discipline such as Statistics, Computer Science, Applied Mathematics, Operational Research with three or more years of relevant work experience.