• Data Scientist, Claims & Operations Emerging Sciences

    The HartfordColumbus, OH 43201

    Job #2818315899

  • Data Scientist - GD08AE

    We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

    The Hartford seeks a Data Scientist within Claims & Operations Data Science to develop machine learning and generative artificial intelligence solutions across a range of strategic initiatives.

    The Claims & Operations Emerging Sciences team is a new team focused on providing deep insights across the policy & claim lifecycles and making adjuster workflows more efficient by leveraging new technologies and analytical capabilities. The Emerging Sciences team builds integrated and interactive solutions with a toolkit including generative AI, natural language processing, computer vision, as well as more traditional machine learning techniques. We deliver value by partnering closely with enterprise enablement and other line of business data science teams to help build a consistent approach to architecture and practices, while tailoring solutions to our customers' unique needs in accuracy, transparency, and scalability.

    As a Data Scientist, you will participate in the entire solution lifecycle. You'll partner with cross-functional business and technical partners to understand business strategies and help design, develop, implement, and evolve modeling solutions. We use the latest generative models, machine learning methods, MLOps deployment methods, and Agile delivery frameworks to build innovative and efficient solutions that maximize business value. This cutting edge and forward focused organization presents the opportunity for collaboration, growth, self-organization within the team, influencing decision-making, and visibility as we focus on continuous business value delivery.

    This role will have a Hybrid work arrangement, with the expectation of working in an office location (Hartford, CT, Charlotte, NC, Chicago, IL, Columbus, OH) 3 days a week (Tuesday through Thursday).

    Responsibilities

    • Create statistical models, algorithms, and machine learning techniques to achieve financial objectives and solve business problems

    • Participate in reviewing work with business partners and team members on an ongoing basis to calibrate deliverables against expectations

    • Assist in identifying and assessing the value of new analytical and generative techniques to ensure ongoing competitive advantage

    • Participate in the creation and deployment of long-term tools to continually evolve the business

    • Execute tasks and projects to support successful implementation of targeted business strategies

    • Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources in your area of expertise

    • Become and remain current on research techniques and become familiar with state-of-the-art tools in generative AI

    • Provide economic, qualitative, and statistical support to ensure accuracy of characteristics and metrics being applied to business decisions

    • Execute work according to best practices of our Data Science and Data Engineering workflows

    Qualifications

    • 2+ years of relevant experience recommended, including education

    • Preference for Master's or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or progress towards a relevant professional designation

    • Experience in statistical modeling, inference, and building machine learning algorithms in Python

    • Exposure to SQL and navigating datasets

    • Exposure to Unix and Git

    • Exposure to the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation

    • Exposure to leveraging generative artificial intelligence (e.g. large language models, image generation, or multimodal generative models) a plus

    • Exposure to building modeling solutions in cloud-native environments, such as Sagemaker, a plus

    • Able to communicate effectively with both technical and non-technical teams

    • Able to translate complex technical topics into business solutions and strategies

    • Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

    Compensation

    The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

    $87,120 - $130,680

    Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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    Human achievement is at the heart of what we do.

    We believe that with the right encouragement and support, people are capable of achieving amazing things.

    We put our belief into action by ensuring individuals and businesses are well protected, and by going even further - making an impact in ways that go beyond an insurance policy.

    Nearly 19,000 employees use their unique talents in careers that span a variety of disciplines - from developing the latest technology to creating and promoting our products to evaluating future financial risks.

    We're also committed to programs that drive education and support volunteerism, which put human beings first. We do it because it's the right thing to do, and because when our customers, communities and employees succeed, we all do.

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