Data & AI Analyst: Production ML & LLM Solutions

L.E.K. Consulting; Boston (MA); Hybrid; USD 80,000 - 100,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with employer contribution

HSA contributions

Hybrid work model

Paid time off

Job summary

L.E.K. Consulting in Boston seeks an Associate Data & AI Analyst to design, deploy, and maintain AI-driven data solutions across the full lifecycle, from data pipelines to cloud-hosted applications.

You will work with stakeholders to translate business needs into scalable, production-ready systems, applying sound judgment on when AI is the right tool, while ensuring code quality and governance.

Qualifications

• Relevant data/ML experience in ML, data engineering, or AI app development.
• Strong coding in Python and SQL with production-grade code.
• Experience with LLMs, prompt engineering, and RAG.
• Experience with data pipelines and lakehouse architectures.
• Familiarity with Azure, Docker, web apps, and CI/CD.
• Understanding of vector databases and search tech.

Responsibilities

• Design and deploy ML and LLM-based solutions addressing business needs.
• Build data pipelines and lakehouse using Fabric and Azure.
• Develop RAG solutions using search indexes and vector DBs.
• Prepare datasets to improve model performance.
• Develop and deploy internal web apps and dashboards on Azure.
• Evaluate model outputs and tackle issues like hallucination and bias.
• Integrate AI with enterprise APIs and data sources.
• Maintain code quality with Git, reviews, docs, DevOps.
• Translate stakeholder requirements into scalable designs and communicate trade-offs.

Skills

Python

SQL

Data engineering

AI app development

LLMs

RAG

Azure

Docker

CI/CD

Communication

Education

Bachelor's degree in CS/DS/Engineering

Tools

Microsoft Fabric

Vector databases

Git

Web app deployment

Job description

L.E.K. Consulting in Boston seeks an Associate Data & AI Analyst to design, deploy, and maintain AI-driven data solutions across the full lifecycle, from data pipelines to cloud-hosted applications.

You will work with stakeholders to translate business needs into scalable, production-ready systems, applying sound judgment on when AI is the right tool, while ensuring code quality and governance.