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Hartford
Hartford

Insurance and financial services

GEN AI Sr Data Scientist/Data Scientist

직무데이터 사이언스
경력시니어급
위치Hartford; Columbus; Charlotte; Chicago
근무오피스 출근
고용정규직
게시3주 전
지원하기
  • Sr Data Scientist

  • GD07AE

  • 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.

Senior Data Scientist – AI Horizontal Products

Step into the future with The Hartford as a Senior Data Scientist, where Generative AI is a core strategic capability—it’s central to our enterprise strategy. Join a team that’s pioneering AI‑driven products across underwriting, claims, and customer service, transforming how we operate and make decisions at scale.

As part of our Horizontal AI Products Team, you will investigate emerging models, architectures, and techniques; design rigorous evaluation frameworks; and prototype new products that inform how GenAI is operationalized across the organization. This position is ideal for someone who is intellectually curious, technically deep, and motivated by advancing the state of practice in enterprise Generative AI.

This position offers a Hybrid or Remote work arrangement. Candidates living near one of our locations are expected to work in the office three days per week (Tuesday–Thursday).

Research & Technical Responsibilities

  • Conduct applied research in Generative AI, exploring emerging foundation models, architectures, and inference strategies to address enterprise AI use cases.
  • Lead investigation and experimentation across areas such as:
  • Agent‑based and multi‑step reasoning workflows
  • Retrieval‑augmented generation (RAG)
  • Long‑context modeling and information synthesis
  • Prompting strategies and controllability of generative outputs
  • Design and execute rigorous experimental frameworks to evaluate model quality, robustness, latency, cost, and reliability using:
  • Automated metrics
  • Human‑in‑the‑loop feedback
  • LLM‑as‑a‑judge and comparative evaluation methodologies
  • Create benchmarks and build reproducible pipelines to compare vendor models, open‑source alternatives, and internal approaches.
  • Rapidly prototype research ideas using modern GenAI tooling such as:
  • Vertex AI / Google Agent Development Kit
  • Lang Chain / Lang Graph
  • RAG frameworks
  • Hugging Face ecosystems
  • OpenAI APIs
  • Translate research findings into deployable GenAI capabilities, working closely with engineering and MLOps teams to ensure scalability, observability, and responsible AI practices.
  • Contribute to the enterprise GenAI roadmap by identifying gaps, risks, and opportunities informed by ongoing research and industry trends.
  • Partner with stakeholders across Data Science, Technology, and Business teams to align research directions with real‑world operational challenges.

Qualifications

  • Masters and 5+ years of industry experience OR PhD and 3+ years of industry experience in machine learning or data science and with 1+ years focused on GenAI.
  • Strong proficiency in Python and modern AI/ML frameworks
  • Demonstrated experience designing experiments, running evaluations, and drawing conclusions from empirical results.
  • Hands‑on experience with Generative AI frameworks and platforms, including Vertex AI, ADK, Lang Chain/Lang Graph, RAG pipelines, Hugging Face, and OpenAI APIs.
  • Deep understanding of:
  • Agent workflows and tool‑augmented LLMs
  • Prompt engineering and model controllability
  • Retrieval‑augmented generation (RAG) design trade‑offs
  • Generative model evaluation and benchmarking techniques
  • Experience collaborating with engineering and MLOps teams to transition prototypes into production systems.
  • Strong written and verbal communication skills, including the ability to explain research findings, limitations, and trade‑offs to both technical and non‑technical audiences.
  • Authorization to work in the United States without company sponsorship. STEM OPT I‑983 Training Plan endorsement is not supported for this role.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:

$90,160 - $166,080

The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience.

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

About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits

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Hartford 소개

Hartford

Hartford

Bootstrapped

The Hartford Insurance Group, Inc., known as The Hartford, is a U.S.-based insurance company. The Hartford is a Fortune 500 company headquartered in its namesake city of Hartford, Connecticut. It was ranked 162nd in Fortune 500 in 2024.

51-200

직원 수

Paris

본사 위치

리뷰

10개 리뷰

3.7

10개 리뷰

워라밸

4.2

보상

2.8

문화

4.3

커리어

2.5

경영진

3.2

68%

지인 추천률

장점

Good work-life balance and flexible hours

Strong team culture and supportive colleagues

Excellent health benefits and vacation time

단점

Low pay and uncompetitive salary

Limited career advancement and growth opportunities

Poor communication from upper management

연봉 정보

62개 데이터

Mid/L4

Senior/L5

Mid/L4 · MANAGER DATA ENGINEERING

3개 리포트

$203,855

총 연봉

기본급

$156,458

주식

-

보너스

-

$203,855

$203,855

면접 후기

후기 3개

난이도

3.3

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 67%

부정 33%

면접 과정

1

Phone Interview

2

Video Interview

3

Analyst Interview

4

Trader Interview

5

Vice President Interview