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.
• Experience in statistical modeling, machine learning, and advanced analytics using Python, including pandas, NumPy, scikit-learn, and strong SQL for complex data exploration, feature engineering, and knowledge preparation; familiarity with PyTorch and/or TensorFlow preferred.
• Experience across the end-to-end modeling and analytics lifecycle, including requirements gathering, experiment design, offline evaluation, and basic production monitoring and validation of AI and BI solutions.
• Solid understanding and practical application of core machine learning, deep learning, and natural language processing algorithms and architectures.
• Experience designing and implementing business intelligence and semantic layer solutions, including dimensional modeling, fact tables, metrics definition, and operating within data warehouse or data lake environments.
• Experience designing and operationalizing evaluation and monitoring strategies, including test set creation (gold and/or synthetic), defining and tracking metrics such as classification, forecasting, ranking/IR, RAG faithfulness and truthfulness, and customer or operational KPIs, with support for A/B testing and drift detection.
• Experience designing, developing, and deploying conversational AI solutions, including chatbots, virtual assistants, intelligent agents, and Retrieval-Augmented Generation (RAG) pipelines.
• Experience working with unstructured data, including document parsing and OCR fundamentals, robust text normalization, metadata and lineage awareness, and PII detection or redaction considerations for insurance documents.
• Experience working with cloud-based AI and analytics platforms such as Google Vertex AI, AWS SageMaker or Bedrock, or Azure AI Services, supporting experimentation, deployment, and conversational AI use cases.
• Experience using Git and Unix-based environments, building reproducible notebooks or pipelines, and applying basic container and cloud concepts to support reliable analytics and AI workflows.
• Experience communicating complex technical designs, trade-offs, evaluation results, and risks to both highly technical and non-technical business audiences, translating insights into clear business outcomes and strategy.
• Foundational knowledge of insurance products, processes (including underwriting, claims, and pricing), and regulatory environments, with demonstrated ability to apply analytics and AI solutions within a regulated industry context.
• Experience with advanced NLP and Generative AI capabilities, including embeddings, hybrid and dense retrieval strategies, advanced chunking, prompt engineering, structured outputs, and integrating knowledge graphs into RAG solutions for improved grounding.
• Experience or exposure to advanced GenAI applications in insurance, such as compliance-aware prompt engineering, document generation, objection response automation, synthetic data generation for low-frequency events, and customer sentiment modeling from surveys, call transcripts, or inspection notes.
• Experience working within enterprise AI governance frameworks, aligning conversational AI and analytics solutions with compliance, privacy, documentation, and ethical standards.
About Us | Our Culture | What It’s Like to Work Here
Skills Required
- Experience with statistical modeling, machine learning, advanced analytics, Python, pandas, NumPy, scikit-learn, and complex SQL.
- Experience across the end-to-end modeling and analytics lifecycle, including requirements gathering, experiment design, offline evaluation, production monitoring, and validation.
- Practical knowledge of machine learning, deep learning, and natural language processing algorithms and architectures.
- Experience designing business intelligence and semantic layer solutions, including dimensional modeling, fact tables, metrics, data warehouses, and data lakes.
- Experience designing evaluation and monitoring strategies using test sets, classification, forecasting, ranking, RAG, customer, and operational metrics, with A/B testing and drift detection.
- Experience designing, developing, and deploying conversational AI solutions, chatbots, virtual assistants, intelligent agents, and RAG pipelines.
- Experience with unstructured data, document parsing, OCR, text normalization, metadata, lineage, PII detection, and redaction.
- Experience with cloud AI and analytics platforms such as Google Vertex AI, AWS SageMaker, AWS Bedrock, or Azure AI Services.
- Experience using Git and Unix-based environments, reproducible notebooks or pipelines, containers, and cloud concepts.
- Ability to communicate technical designs, trade-offs, evaluation results, risks, and business outcomes to technical and non-technical audiences.
- Foundational knowledge of insurance products, underwriting, claims, pricing, and regulated industry environments.
- Experience with advanced NLP and generative AI, including embeddings, hybrid and dense retrieval, chunking, prompt engineering, structured outputs, and knowledge graphs.
- Experience or exposure to advanced generative AI applications in insurance, including compliance-aware prompting, document generation, objection response automation, synthetic data, and sentiment modeling.
- Experience working within enterprise AI governance frameworks covering compliance, privacy, documentation, and ethical standards.
- Familiarity with PyTorch and/or TensorFlow.
The Hartford Financial Services Group, Inc. Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Hartford Financial Services Group, Inc. and has not been reviewed or approved by The Hartford Financial Services Group, Inc..
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Retirement Support — A 401(k) with matching plus an additional company contribution, alongside an employee stock purchase plan and no‑cost financial planning, signals robust long‑term savings support. HSAs/FSAs and related financial tools further strengthen overall financial well‑being.
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Leave & Time Off Breadth — At least 25 days of PTO to start, options to buy or roll over time, and paid parental leave indicate broad time‑off support. Paid leave for organ and bone marrow donation and generous disability coverage extend protection for significant life events.
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Healthcare Strength — Multiple medical, dental, and vision options with the company covering most medical and dental premiums reflect strong core health coverage. Wellness programs, fitness reimbursements, well‑being credits, and accessible behavioral health services expand depth and accessibility.
The Hartford Financial Services Group, Inc. Insights
What We Do
Human achievement is at the heart of what we do. We put our belief into action by not only ensuring individuals and businesses are well protected, but by going even further – making an impact in ways that go beyond an insurance policy
