Data Scientist

Data Scientist

📍 Location: United States

🏢 Industry: Financial services

💼 Work Setting: Remote

Are you passionate about applying AI, machine learning, and advanced analytics to solve real-world business challenges?

Great Gray is seeking a Data Scientist to join its growing Data Science & AI Team. This role blends traditional data science, machine learning engineering, generative AI, and software development to build scalable, production-ready solutions that drive business value in the retirement services industry.

The ideal candidate combines strong Python development skills, AI/ML expertise, cloud experience, and a collaborative mindset focused on innovation, quality, and continuous improvement.

Key Responsibilities

Machine Learning Development

• Build, train, test, and deploy machine learning models for business applications.
• Develop scalable data pipelines and analytical workflows.
• Improve model performance, reliability, and operational efficiency.
• Monitor model behavior and address drift or performance issues.
• Support end-to-end machine learning lifecycle management.

Generative AI & Large Language Models (LLMs)

• Design and deploy LLM-powered applications.
• Build and enhance Retrieval-Augmented Generation (RAG) architectures.
• Develop:
• Prompt Engineering Strategies
• Embedding Pipelines
• Vector Database Integrations
• Evaluation Frameworks
• Optimize AI solutions for accuracy, relevance, and scalability.
• Evaluate emerging foundation models and AI capabilities.

Agentic AI Development

• Build intelligent agent-based systems capable of:
• Tool Usage
• Workflow Automation
• Multi-Step Reasoning
• Complex Decision Support
• Utilize orchestration frameworks to automate business processes.
• Improve agent performance, governance, and reliability.

Data Analysis & Business Insights

• Conduct exploratory data analysis (EDA).
• Identify trends, patterns, anomalies, and opportunities within datasets.
• Translate findings into actionable business recommendations.
• Support data-driven product and strategy decisions.
• Communicate analytical outcomes to technical and business audiences.

Data Visualization & Reporting

• Create dashboards and visual analytics solutions.
• Present key metrics and performance indicators effectively.
• Deliver insights in a clear and business-friendly format.
• Enable stakeholders to make informed decisions through data storytelling.

AI/ML Operations & Quality

• Establish best practices for:
• Experiment Tracking
• Model Evaluation
• Reproducibility
• Code Quality
• Monitoring
• Diagnose and resolve complex data, pipeline, and modeling issues.
• Ensure production-grade reliability and maintainability.
• Support continuous improvement in model performance.

Innovation & Emerging Technologies

• Research and evaluate new developments in:
• Artificial Intelligence
• Generative AI
• Machine Learning
• Agentic AI
• Cloud AI Platforms
• Explore technologies such as:
• Azure AI Foundry
• AWS Bedrock
• Cursor
• Claude
• Recommend innovative approaches that advance organizational capabilities.

Cross-Functional Collaboration

• Partner with business, technology, and product teams.
• Translate business requirements into analytical solutions.
• Collaborate in Agile development environments.
• Contribute to architectural discussions and technical decision-making.
• Support enterprise AI and data science initiatives.

Qualifications

Required Experience

• 3+ years of experience as:
• Data Scientist
• Machine Learning Engineer
• Applied AI Engineer
• Experience delivering production-grade machine learning solutions.
• Strong background in building scalable AI and analytics products.
• Experience collaborating with cross-functional teams.

Technical Skills

Programming & Data Science

• Python
• Pandas
• NumPy
• Scikit-Learn
• FastAPI
• SQL

Machine Learning

• Supervised Learning
• Model Deployment
• Model Monitoring
• Feature Engineering
• Predictive Analytics
• Production ML Systems

Generative AI

• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Embedding Models
• AI Evaluation Frameworks

Agentic AI

• Agent Workflows
• Tool Integration
• Multi-Step Reasoning Systems
• AI Orchestration Frameworks
• Autonomous Decision Support

Cloud Platforms

• Microsoft Azure
• Amazon Web Services (AWS)
• Cloud-Based AI Services
• Managed Machine Learning Platforms

Preferred Qualifications

• Experience with:
• Azure AI Foundry
• AWS Bedrock
• Databricks
• PostgreSQL
• Microsoft SQL Server
• Familiarity with:
• Cursor
• Claude
• AI-Assisted Software Development
• Experience building cloud-native AI applications.
• Understanding of financial services, retirement services, or fintech environments.
• Entrepreneurial mindset and comfort working in evolving environments.

Technology Stack

Data & AI

• Python
• Pandas
• NumPy
• Scikit-Learn
• FastAPI
• Databricks

Databases

• Microsoft SQL Server
• PostgreSQL

Cloud

• Microsoft Azure
• AWS

Development Tools

• GitHub
• Docker
• Cursor
• SonarQube

Front-End

• Angular
• React

Back-End

• C# .NET

Core Competencies

• Data Science
• Machine Learning
• Generative AI
• Large Language Models (LLMs)
• Agentic AI
• Retrieval-Augmented Generation (RAG)
• Python Development
• SQL
• Cloud AI Platforms
• FastAPI
• Data Visualization
• Predictive Analytics
• Model Deployment
• Analytical Problem Solving
• Cross-Functional Collaboration