Data Scientist

Hartford Funds is seeking a thoughtful and versatile Data Scientist to join our growing Emerging Tech and AI team. This role combines core modeling and analytics expertise with a strong awareness of modern AI, automation, and workflow technologies. Ideal candidates are hands-on with data, comfortable with ambiguity, and motivated to create value through intelligent systems and automation. Key Responsibilities Develop and deploy statistical and machine learning models to solve a range of business problems, including forecasting, classification, segmentation, and causal inference. Collaborate across business and technology teams to scope projects, identify opportunities, and deliver actionable insights. Contribute to AI and automation-related initiatives, helping evaluate and implement GenAI and workflow solutions. Support scalable data solutions using modern cloud tools and APIs, and help maintain analytical and data science codebases. Education Bachelor’s degree in Statistics, Computer Science, Mathematics, or a related discipline. Master’s degree in Statistics, Computer Science, Mathematics, or a related discipline. Experience Minimum 4 years of hands-on experience in data science or a related field. Preferred 6+ years of hands-on experience in data science or a related field. Required Skills Strong foundation in statistical modeling and machine learning, including regression, time series forecasting, tree-based algorithms, optimization, and causal analysis. You should be comfortable applying the right methods to the right problems. Strong Python and SQL. Familiarity with R is a plus, especially for supporting legacy code. Understanding of the Microsoft Copilot ecosystem; including Copilot Studio, Azure Foundry, and prompting best practices. Experience building or configuring Copilot agents is a huge plus. Experience working with Snowflake or a similar cloud data platform. Ability to work with APIs, write modular and reproducible code, and support basic data engineering tasks (e.g., pipeline design, version control). Preferred Qualifications Familiarity with robotic process automation tools such as UiPath, Power Automate, or similar platforms. Awareness of workflow automation tools (e.g., n8n, Apache Airflow, etc) and how they integrate with predictive models or LLMs. Understanding of how automation, GenAI, and decision systems can be orchestrated to create agentic or semi-autonomous solutions. Exposure to MLOps or DevOps practices such as CI/CD pipelines, model versioning, or containerization. General understanding of Salesforce and its role in enterprise data ecosystems. Additional Qualities We Value Strong communication skills with the ability to translate technical work into clear, business-relevant insights. Ability to balance hands-on technical development with broader strategic thinking. Curiosity about emerging technologies and a pragmatic approach to applying them in real business contexts. Seniority level

Mid-Senior level Employment type

Full-time Job function

Information Technology Industries: Investment Management and Financial Services

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