Data Scientist

Great Gray Trust Company

Data Scientist responsible for building AI/ML models to enhance retirement service solutions. Working collaboratively within a team to drive data-driven insights and improve client experience.

Posted 7/24/2026full-timeRemote • California, Colorado, Connecticut, District of Columbia, Florida, Illinois, Maryland, Massachusetts, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Virginia • 🇺🇸 United StatesMid-LevelSenior💰 $90,000 - $120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building, training, and deploying machine learning models and data pipelines using Python, with a strong focus on scalability, reliability, and data-driven insights. Proficient in SQL and experienced in cloud environments, capable of translating business requirements into high-quality analytical solutions.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingData Pipeline ConstructionSQL ProficiencyCloud Environment Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisModel EvaluationData VisualizationPrompt EngineeringEmbedding StrategiesExploratory Data AnalysisModel ServingExperiment TrackingReproducibility

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

PandasNumPyScikit-learnFastAPIAzureAWS

Industry Keywords

Data ScienceML EngineeringRAG PipelinesAgentic AI SystemsOrchestration Frameworks

Tech Stack

Tools & technologies

AWSAzureCloudNumpyPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

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.
Collaborate closely with cross-functional teams to translate business requirements into data-driven insights, models, and high-quality analytical solutions.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Competitive compensation package
Group medical, dental and vision insurance
Employer-paid life and disability insurance
Annual well-being stipend
Eligible employees may also contribute to a 401(k) plan with an advantageous employer contribution model