Principal Data Scientist

About the Role

Key Responsibilities

• Support The Hartford's AI innovation strategy to identify and implement high-end use cases, ensuring alignment with business objectives and emerging industry trends.
• Support cutting-edge AI vision and roadmap for the enterprise to make The Hartford a leader in using AI for the insurance industry.
• Partner with stakeholders internal to the Data Science organization, Technology organization and business organization, aligning with business objectives and driving innovation to improve productivity and efficiency of underwriting and sales efforts.
• Lead end-to-end AI projects from problem formulation to model deployment, integrated into a broader portfolio of advanced analytics.
• Drive the development of state-of-the-art AI/ML models with a focus on, AI, GenAI, Agent architecture-based chat solutions, Automated scenario simulation and model optimization.
• Develop LLM models and data-driven solutions to optimize business processes, improve process transparency and drive data-driven decision making.
• Design and conduct experiments, tests, and causal inference analysis to evaluate the effectiveness of interventions and initiatives.
• Champion the integration of AI solutions within The Hartford's AI platform to maximize reuse, scalability, and governance.
• Closely work with cross-functional teams to define, prioritize, and implement features, infrastructure, processes, and workflows.
• Stay up to date with the latest developments in AI, Large Language Models, Machine Learning, and related fields.
• Evaluate emerging technologies for potential adoption.
• Support development of a high-performing enterprise AI team, fostering individual growth and technical excellence.
• Provide strategic AI leadership, influence stakeholders across the organization, and drive transformative AI initiatives that enhance decision-making, automation, and business impact.
• Provide training and mentoring to team members on AI & GenAI technologies, agentic workflows, and implementation strategies.
• Share knowledge and best practices to foster a culture of innovation and continuous improvement.

Requirements

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Engineering or a related field is preferred with 4+ years of professional experience in AI with strong foundation in Machine Learning.
• Masters or Bachelors in Computer Science or related areas with 12+ years of industry experience would also be considered.
• Ability to execute on a vision for AI initiatives and align them with business objectives.
• Strong understanding of AI trends and how to position AI as a strategic asset within the organization.
• Experience in Data Science, Agent architecture (CrewAI, Semantic Kernel, Autogen, Prompt Flow), Large Language Models (Commercial and Open Source), LangChain, Retrieval Augmented Generation, Vector Databases, and Machine Learning models.
• Proficiency in one or more general purpose programming languages like Python, Java and Machine learning libraries, e.g., PyTorch and scikit-learn.
• Experience with both NoSQL and SQL database for data manipulation and querying.
• Sound Knowledge of Docker, Kubernetes, Cloud based ML/LLMOps tools like SageMaker / ML Studio / Vertex AI.
• Experience with GCP, Cloud AI, Vertex AI, and Big Query strongly preferred.
• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders across the enterprise.
• Experience creating production environment data analytics and applications.

Nice to Have

• Insurance industry experience would be a plus.

Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Engineering or a related field (preferred).
• 4+ years of professional experience in AI (preferred).
• Masters or Bachelors in Computer Science or related areas with 12+ years of industry experience (considered).

Benefits & Perks

• 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.