Data Associate Jobs in Springfield, MA (NOW HIRING)

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The Hartford seeks an Associate Data Scientist within the Applied AI and Analytics Claims department to develop machine learning and artificial intelligence solutions across a range of strategic initiatives.
The Workers Compensation & Employee Benefits Claims Data Science Team engineers end-to-end analytic and machine learning solutions to optimize operational efficiency, customer and claimant experience.
As a Data Scientist, you will participate in the entire model lifecycle partnering with cross-functional business and technical partners to understand business strategies and design, develop, implement, and evolve modeling solutions. We use the latest technologies, machine learning methods, MLOps, 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 data delivery.
This role can have a Hybrid or Remote work schedule. Candidates who live near one of our locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office should maintain their current work arrangement with the expectation of coming into the office as business needs arise.
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 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
• 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 applicable to your function
• Provide economic, qualitative, and statistical support to ensure accuracy of characteristics and metrics being applied to business decisions

Qualifications:

• 2+ years of relevant experience recommended
• 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
• Experience in SQL and navigating databases to extract relevant attributes
• Experience in Unix and Git
• Experience in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation
• Exposure to building modeling solutions in cloud-native environments, such as Sagemaker or Vertex AI, a plus
• Understanding of prompt engineering, retrieval-augmented generation (RAG), agent workflow, and LLM evaluation is a plus

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:

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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