Data Scientist

Why Great Gray? At Great Gray Group, we strive to set the bar for the retirement services industry. Our goal is to deliver advanced retirement solutions that combine our core fiduciary services with robust investment options, innovative technology, and dedicated client service. We focus on making choices clearer, transitions smoother, and the client experience more delightful. Complacency isn't in our vocabulary. Every day, we look for opportunities to better serve our clients, be an excellent business partner, and earn the trust of those who rely on us.

The Role Great Gray is looking to add a Data Scientist onto our Data Science & AI Team. The data scientist we seek comes with strong experience in Python and its data science ecosystem (pandas, NumPy, PyDantic, FastAPI) and hands-on experience building and deploying AI/ML solutions. You will be working collaboratively within an agile team, contributing to architectural decisions, and championing best practices in software development. If you are passionate about applying data science and AI to solve real business problems, thrive in a collaborative environment, and care deeply about the quality and impact of your work you will do well here. Our team members are expected to take full ownership of our products as well as embrace efficiency and continuous improvement. We are not looking for a few rock stars, but rather very strong contributors who bring curiosity, rigor, and a collaborative spirit to every problem they tackle. This is an exciting opportunity to grow alongside Great Gray as we expand our data science and AI capabilities. Your ability to develop models, surface insights, and collaborate across teams will directly shape how we serve the retirement market. Location This position will work remote from the United States. Please note that remote employment in this role is restricted to candidates residing in states where Great Gray is currently registered as an employer. These states are limited to: CA, CO, CT, DC, DE, FL, GA, IL, IN, MA, MD, MI, MN, NC, NH, NJ, NV, NY, OH, PA, RI, SC, TN, TX and VA. Visa sponsorship or transfer of an existing visa is not available for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship or transfer. Responsibilities Build, train, and deploy machine learning models and data pipelines using Python, pandas, NumPy, and scikit-learn, ensuring scalability and reliability in production. Design, implement, and continuously improve LLM-powered applications and Retrieval-Augmented Generation (RAG) pipelines, including prompt engineering, embedding strategies, vector store integration, and evaluation frameworks. Build and iterate on agentic AI systems that leverage tool use, multi-step reasoning, and orchestration frameworks to automate complex workflows and decision-making processes. Conduct exploratory data analysis (EDA) to uncover trends, patterns, and anomalies that inform business decisions and product strategy. Design and build data visualizations and dashboards that communicate key metrics and insights to both technical and non-technical stakeholders. Diagnose and resolve complex data and model issues, minimizing drift and continuously improving pipeline efficiency and model accuracy. Drive technical excellence through rigorous model evaluation, identifying opportunities for improvement, and enforcing best practices in code quality, experiment tracking, and reproducibility. Contribute to innovation by exploring emerging AI/ML technologies, LLM integrations (Azure AI Foundry, AWS Bedrock), and agentic tooling (Cursor, Claude) to keep our solutions at the cutting edge. Collaborate closely with cross-functional teams to translate business requirements into data-driven insights, models, and high-quality analytical solutions. A strong analytical mindset and the ability to translate complex data findings into clear business recommendations. Strong collaboration skills, fostering an environment of shared learning, experimentation, and innovation. A passion for rigorous data science practices, reproducible research, and driving excellence in model development and deployment. The ability to balance multiple modeling and research priorities while maintaining high-quality, production-ready outcomes. Complete other related duties as assigned Required Qualifications & Experience Exhibits our Great Gray attributes: Growth Mindset, Disciplined Curiosity, Grit, Results Ownership, Collaboration. 3+ years of experience as a Data Scientist or ML Engineer, with a track record of delivering production-grade models. Proficiency in Python and the core data science stack: pandas, NumPy, scikit-learn, and FastAPI. Strong proficiency in SQL and experience querying large datasets in cloud environments (Azure, AWS). Experience building and deploying ML models and APIs, including familiarity with model serving and monitoring. Preferred Qualifications & Experience Experience with large language models and AI platforms such as Azure AI Foundry or AWS Bedrock. Experience with AI-assisted development workflows using tools like Cursor and Claude. A growth mindset with an eagerness to learn new technologies and adapt to evolving challenges. Comfortable navigating ambiguity. Entrepreneurial mindset to bring best practice ideas to the team. Hands-on experience with Azure and AWS services, including cloud-based ML workflows and managed AI services. Tech Stack Our current tech stack is a blend of existing and next-gen tools/languages, and like our company itself, our software is always evolving. Frontend: Angular, React Backend: C# .NET Data Layer: MSSQL, Python, Postgres, Databricks Infrastructure: Azure cloud Tooling: Cypress, Docker, GitHub, Cursor, SonarQube Base Pay Range* $90,000 - $120,000 *This base pay range is subject to change and may be modified in the future. The pay range displayed above is the base pay compensation range that Great Gray expects to pay for this position at the time of this posting. Individual compensation within this range, or that may warrant a provision for pay beyond this range, depends on multiple factors, including, but not limited to, candidate’s prior education and relevant work experience and training as well as position location and local market demands. Our pay-for-performance culture also includes participation in an annual incentive bonus plan for this position which is not included in the ‘Base Pay Range’ noted above.