Data Scientist

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 help others accomplish theirs too. The Hartford seeks a Data Scientist within a multidisciplinary actuarial/data science team responsible for designing and delivering powerful analytical insights utilizing statistical modeling, machine learning, and data engineering techniques to enhance and overhaul core actuarial processes.

You will work with data scientists, data engineers, and actuaries in a highly collaborative, cross‑functional environment, partnering with business and technical stakeholders to understand strategies, design, develop, implement, and evolve loss‑modeling solutions. Strong communication skills are required, and you should enjoy researching state‑of‑the‑art solutions and learning new tools and languages as needed.

• Create statistical models, algorithms, and machine learning techniques to enhance traditional actuarial processes and assumptions
• Think creatively to envision how we can enhance long‑standing actuarial methodology using statistical modeling and machine learning techniques
• Use R and/or Python to build, maintain, and support loss models across different lines of business
• Participate in reviewing work with business partners and team members on an ongoing basis to calibrate deliverables against expectations and effectively translate results to business initiatives
• Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources
• 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

• 2+ years of relevant experience recommended
• Preference for at least one of:
  Master’s in Statistics, Applied Mathematics, Data Science, Computer Science, Actuarial Science, or a similar analytical field
• Progress towards relevant professional credentials (e.g. FCAS, FSA, CSPA)
• Experience in statistical modeling, inference, and building machine learning algorithms in Python and/or R
• Experience in SQL and navigating databases to extract relevant attributes
• Experience in Unix, Git, Shiny and R Markdown is a plus
• Experience in the end‑to‑end modeling lifecycle, from requirements gathering to monitoring and validation
• Able to communicate effectively with both technical and non‑technical audiences
• High level of independence, but is also a team player that demonstrates a high level of ownership
• Results driven with commitment to meeting deadlines

Hybrid or Remote work arrangement is available based on experience and skillset. Candidates who live near one of our office locations (Columbus, OH; Chicago IL; Hartford CT; or Charlotte NC) are expected to work in the office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office and have appropriate experience may be eligible for a remote work arrangement, with the expectation of coming into an office as business needs arise.

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.

The listed annualized base pay range is $90,160 - $135,240. 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. Other rewards may include short‑term or annual bonuses, long‑term incentives, and on‑the‑spot recognition.

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