The Hartford is looking to develop machine learning and artificial intelligence solutions across a range of strategic initiatives to solve business problems and achieve financial objectives.
Requirements
- Exposure to statistical modeling, inference, and building machine learning algorithms in an analytical programming language like Python or R
- Exposure to building modeling solutions in cloud-native environments, such as Sagemaker, a plus
- Exposure to SQL and navigating databases to extract relevant attributes a plus
- Exposure to Unix and Git a plus
- Able to maintain organized project notes, version history, and technical documentation for team reference
Responsibilities
- Assist in creating statistical models, algorithms, and machine learning techniques to achieve financial objectives and solve business problems
- Assist in identifying and assessing the value of new data sources and analytical techniques to ensure ongoing competitive advantage
- Participate in the creation and deployment of long-term tools to continually evolve the business
- Contribute to the successful implementation of strategies to achieve targeted business objectives
- Remain current on research techniques and become familiar with state-of-the-art tools applicable to your function
- Provide economic, qualitative, and statistical support to ensure accuracy of characteristics and metrics being applied to business decisions
- Prepare and deliver presentations that translate data-driven insights, model results, and recommendations to varying business partners
Other
- Must be authorized to work in the United States without sponsorship now, or in the future
- Must be working towards a Master’s or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field
- Strong communication skills for explaining methodologies, visualizations, and recommendations to non-technical audiences and vice versa
- Participate in reviewing work with business partners and team members on an ongoing basis to calibrate deliverables against expectations
- Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources in your area of expertise
