Sr Data Scientist - GD07AE
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 Senior Data Scientist Employee Benefits Data Science, AI, and Analytics (DSAIA) to develop machine learning and generative artificial intelligence solutions across a range of strategic initiatives.The Employee Benefits DSAIA team is a rapidly growing team focused on providing deep insight, automation, and augmentation across the policy lifecycle for Employee Benefits customers and internal business stakeholders. The EB DSAIA team supports a portfolio across the EB lifecycle, from sales and underwriting to policy installation, renewal, and everything in between. In addition to our existing portfolio of Predictive AI assets, the team is scaling to expand an end-to-end (E2E), AI-driven reimagination of the EB underwriting and service organizations. Our E2E projects will include integrated, interactive solutions with a toolkit including generative AI, natural language processing, computer vision, and predictive 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 across AI products while tailoring solutions to our customers' unique needs in accuracy, transparency, and scalability.As a Senior Data Scientist in the Employee Benefits DSAIA team, you will participate in the entire solution lifecycle. You'll partner with cross-functional business and technical partners to understand business strategies and 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, self-organization within the team, influencing decision-making, and visibility as we focus on continuous business value delivery.Responsibilities:
Create and use statistical models, algorithms, and machine learning techniques to achieve financial objectives, solve business problems, and identify long term opportunities that improve the customer journey
Collaborate and partner with business stakeholders in a way that supports and sustains a culture that treats analytics as a corporate asset
Lead execution of generative AI, machine learning, and predictive modeling projects that focus on internal team collaboration with Data Scientists, Data Engineers, and Product Owners
Support identifying and assessing the value of new analytical and generative techniques and solution patterns to ensure ongoing competitive advantage
Contribute to successful implementation of strategies to achieve targeted business objectives
Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources in your area of expertise
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
Learn/bring best practices to guide the direction of our Data Science and Data Engineering workflows
Qualifications:
5+ years of relevant industry experience recommended
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
Proficiency in statistical modeling, inference, and building machine learning algorithms in Python
Proficiency in SQL and navigating databases to extract relevant attributes
Proficiency in Unix and Git
Proficiency in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation
Experience in leveraging generative artificial intelligence (e.g. large language models, image generation, or multimodal generative models) including model selection and tuning, prompt engineering, and performance evaluation
Experience 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 as well as turn business requirements into a technical solution
Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).
Candidates 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:
$110,720 - $166,080
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
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Every day, a day to do right.
Showing up for people isn't just what we do. It's who we are - and have been for more than 200 years. We're devoted to finding innovative ways to serve our customers, communities and employees-continually asking ourselves what more we can do.
Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable?
That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined.
And while how we contribute looks different for each of us, it's these values that drive all of us to do more and to do better every day.
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