GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.
On behalf of Mercer, GT is seeking a Senior Data Scientist / AI Consultant to partner with multiple teams across the clients organization — transforming fragmented data into actionable insights, and delivering production-ready, LLM-powered solutions that drive Mercer’s AI strategy.
Contract Duration: 6 months (with possible extension until the end of 2026)
About the Client
Mercer is a global consulting leader in advancing health, wealth, and career outcomes for organizations and individuals. Headquartered in New York City, Mercer operates in over 130 countries with more than 25,000 employees and 180+ office locations worldwide. As part of Marsh McLennan, Mercer provides data-driven insights and tailored solutions in areas such as HR transformation, compensation and benefits, workforce analytics, and employee experience. The company fosters a collaborative, inclusive, and purpose-driven culture that values innovation, integrity, and impact.
About the Role
We’re looking for a Senior Data Scientist / AI Engineer with hands-on experience building and deploying LLM-powered solutions. In this role, you will work closely with Mercer’s internal teams to design LLM classification workflows, develop AI agents, and support the company’s broader AI strategy for 2026.
This position requires someone who is comfortable working in fast-moving, exploratory environments — where rapid prototyping, curiosity, and strong engineering fundamentals matter more than heavy MLOps specialization. You will shape and improve LLM applications, define evaluation metrics, and contribute to lightweight production deployments as these solutions mature.
Responsibilities
LLM & Agent Workflow Development
- Build and refine LLM-based classification and automation workflows.
- Develop AI agents using frameworks such as LangChain or Mastra AI.
- Prototype fast, iterate frequently, and adapt solutions as the stack evolves.
Prompt Engineering & Evaluation
- Design, test, and optimize prompts for accuracy and reliability.
- Define appropriate evaluation metrics and data quality standards.
- Implement validation frameworks for LLM outputs.
Lightweight Production Deployment
- Integrate LLM/ML workflows into internal applications or services.
- Deploy solutions through APIs, cloud endpoints, or lightweight microservices.
- Ensure deployed solutions are maintainable, observable, and aligned with business needs.
Data & Engineering Work
- Work with Python in a shared codebase (Git).
- Query and manipulate data using SQL.
- Collaborate with systems using TypeScript / JavaScript (Mastra AI) when needed.
- Work with Databricks and MongoDB for data processing.
Cross-Functional Collaboration
- Work closely with stakeholders across teams to understand requirements.
- Translate business problems into LLM/AI solutions.
- Communicate clearly with technical and non-technical colleagues.
Essential Skills & Experience
- Strong Python engineering skills in production-like environments.
- Hands-on experience building LLM applications end-to-end (OpenAI, HF, LangChain, Mastra AI, etc.).
- Experience developing AI agents and prompt engineering.
- Experience integrating ML/LLM workflows into applications (API, endpoints, microservices).
- Familiarity with SQL and working with modern data platforms (Databricks).
- Comfortable working with evolving tech stacks and iterative prototypes.
- Ability to define, measure, and improve LLM/agent performance metrics.
- Experience working in agile, fast-paced, or startup-style environments.
Nice-to-Have
- Experience with graph databases (e.g., Neo4j).
- Experience with TypeScript/JavaScript for AI workflows.
- Background in building classification systems or automation pipelines.
- Exposure to cloud ML services (Azure ML, Bedrock, Vertex AI).
Interview Process
- GT Recruiter Interview
- Technical Interview with Mercer
- Final Interview with Mercer
