Associate Data & AI AnalystLocation
Boston
Job Description
Overview of RoleThe Associate Data & AI Analyst is a hands-on member of the Data and AI Enablement team, responsible for designing, deploying, and maintaining AI-driven data solutions that solve real business problems. The role works across the full solution lifecycle - from data pipelines and lakehouse architecture through machine learning, large language models (LLMs), retrieval-augmented generation (RAG), and cloud-hosted applications.
This position is well suited to someone who combines strong Python and data skills with practical experience building modern AI solutions. The successful candidate will work closely with technical and non-technical stakeholders to turn business needs into scalable, production-ready systems while applying sound judgment around when AI is - and is not - the right tool.
Key Responsibilities - Design and deploy traditional machine learning and LLM-based solutions that address practical business needs.
- Build and maintain data pipelines and lakehouse architectures using Microsoft Fabric and related Azure services.
- Develop retrieval-augmented generation (RAG) solutions using search indexes, vector databases, and enterprise data sources.
- Prepare, refine, and enrich datasets to improve model performance, evaluation, and reliability.
- Develop and deploy internal web applications and dashboards on Azure, partnering with stakeholders on user experience and KPI visualization where needed.
- Evaluate model and LLM output quality, including common failure modes such as hallucination, bias, prompt injection, context limitations, and reliability issues.
- Integrate AI agents with enterprise APIs, tools, and data sources, including through Model Context Protocol (MCP) where appropriate.
- Maintain high code quality through Git-based workflows, code review, documentation, and DevOps best practices.
- Partner with cross-functional teams to translate ambiguous business requirements into scalable technical designs and clearly communicate trade-offs and AI limitations.
Qualifications - 2-5 years of relevant experience in machine learning, data engineering, AI application development, or a related technical field.
- Strong Python and SQL skills, with experience developing clean, documented, production-quality code.
- Practical experience with large language models, prompt engineering, model evaluation, and retrieval-augmented generation (RAG).
- Knowledge of traditional machine learning techniques such as classification, natural language processing, or sentiment analysis.
- Experience building data pipelines, performing ETL, and working with lakehouse architectures such as Microsoft Fabric.
- Experience with Microsoft Azure, Docker/containerization, web application deployment, and CI/CD practices.
- Understanding of vector databases and search technologies used in RAG solutions.
- Ability to evaluate when AI-based approaches are appropriate and when traditional solutions may be more effective.
- Strong analytical problem-solving skills and the ability to translate stakeholder requirements into scalable technical solutions.
- Clear written and verbal communication skills with both technical and non-technical audiences.
- Bachelor's degree in Computer Science, Data Science, Data Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technology or quantitative discipline.
Preferred Qualifications - Experience with agentic AI architectures, multi-step reasoning pipelines, or Model Context Protocol (MCP).
- Experience with MLOps practices such as model monitoring, versioning, and deployment pipelines.
- Familiarity with data governance, cloud security, and responsible AI practices.
- Experience with orchestration tools such as Azure Data Factory.
- UX or dashboard design sensibility for internal applications and KPI reporting.
- Experience working in a consulting or professional services environment.
What You'll Bring - Sound judgment about the strengths, limitations, and responsible use of AI technologies.
- A structured approach to solving complex and ambiguous business problems.
- Ability to balance model, data, and infrastructure considerations when designing solutions.
- Curiosity, adaptability, and a willingness to work across multiple parts of the modern data and AI stack.
- Strong collaboration skills and the ability to explain technical concepts and trade-offs in practical business terms.
Additional Information - The expected base salary range from this position is $80,000 - $100,000 annually. Actual compensation will be determined based on experience, qualifications, skills, and location. This position may also be eligible for discretionary bonus and a comprehensive benefits package.
- L.E.K. Consulting offers a competitive total rewards package including medical, dental, vision, life and disability insurance, 401(k) with employer contribution, HSA contributions (where applicable), paid time off, and other firm-sponsored benefits.
- This role is based in our Boston office and follows our hybrid work model for U.S. offices. We require employees to be in their assigned home office Tuesday, Wednesday, and Thursday each week, as well as the first Friday of each month.
- Applicants must be legally authorized to work in the United States on a permanent basis without the need for employer sponsorship. Unfortunately, we are unable to consider candidates requiring visa sponsorship, including but not limited to H-1B, TN, F-1 (OPT/CPT/STEM), or other work authorization.
- For more information and to apply, please visit: https://www.lek.com/careers/apply
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