Data Scientist

L.E.K. Consulting; Boston (MA); Hybrid; USD 110,000 - 120,000; Full time

Benefits offered by this job

Discretionary bonus

401(k) with employer contribution

HSA contributions

Job summary

L.E.K. Consulting is seeking a Data Scientist to join the DDA practice within the Data Science & Engineering team in a hybrid role based in Boston, MA.

You will help deliver end-to-end analytics and machine learning, including LLM-based solutions, across client engagements and L.E.K.’s proprietary IP. Take data science work from conceptualization through deployment, deploying models in clients’ cloud environments with emphasis on scalability and reliability, and support interpreting results to

Qualifications

• 2+ years of applied data science with ML foundation.
• Proficiency in Python, Spark, SQL and ML libraries.
• Experience deploying ML models in cloud environments.
• Competence with MLOps, CI/CD and model monitoring.
• Ability to communicate across technical and non-technical audiences.
• Prior exposure to AI/LLM-based analytics and data warehousing.

Responsibilities

• Develop and deploy ML models with focus on scalability and reliability.
• Interpret results and embed insights into client workflows.
• Handle multiple engagements and complex analytics tasks.
• Build data apps and visuals using current ML approaches.
• Guide proposals and ensure alignment with delivery teams.

Skills

2+ years

Python

Spark

SQL

MLOps

LangChain

AWS/Azure/GCP

CI/CD

Excel

PowerPoint

Education

Quantitative degree (Statistics, CS, DS, Math, OR, Engineering, Economics)

Tools

Sagemaker

Azure ML

Kubernetes

Airflow

LangChain

Excel

PowerPoint

Job description

L.E.K. Consulting is seeking a Data Scientist to join its DDA (Data, Digital, and AI) practice within the Data Science & Engineering team. In this hybrid role based in Boston, MA, you will help deliver end-to-end analytics and machine learning, including LLM-based solutions, across client engagements and L.E.K.’s proprietary IP.

What you’ll do

• Take data science work from conceptualization through deployment, including deploying advanced machine learning models in clients’ cloud environments with a focus on scalability, performance, and reliability.
• Assist clients in using technical models effectively by supporting interpretation of results and integrating insights into their day-to-day business workflows.
• Work on a broad set of complex analytical challenges, sometimes balancing multiple client engagements at once.
• Deliver across the analytical stack: data aggregation and creation, cleaning and manipulation, commercial data science (including geospatial, machine learning, predictive modeling, NLP, and LLMs), and visualization.
• Guide stakeholders through the interpretation of analytical outputs and the integration of data-driven insights.
• Support Managing Directors with developing and scoping client proposals where data science, ML, and AI capabilities are central to delivery.
• Act as a technical interface between the Data Science & Engineering team, consulting partners, and clients, ensuring alignment on fit, feasibility, and delivery expectations.
• Translate technical requirements, outputs, and constraints into clear, actionable language for client-facing presentations and proposals.
• Contribute to the design and commercialization of new offerings spanning data science, ML, agentic AI, and LLM-powered analytics.
• Help build state-of-the-art analytical apps using up-to-date machine learning approaches to solve complex problems.
• Collaborate with a range of stakeholders to continuously improve apps, service lines, and proprietary data assets.
• Provide technical expertise and thought leadership on analytical tools, services lines, and proprietary data assets, and help develop these areas when applicable.
• Uphold best-in-class standards in app development, software and data integrity, ensuring solutions are scalable and maintainable.
• Support commercialization efforts and the upskilling of staff on relevant software, tools, and techniques.

What you’ll bring

• At least 2 years of experience in applied data science with a solid foundation in machine learning, statistical modeling, and analysis.
• Strong knowledge and fluency across tools such as Python (data science and ML libraries including scikit-learn, TensorFlow, PyTorch), Spark, and SQL.
• Technical understanding of machine learning algorithms, including performing data science techniques such as classification models, clustering analysis, time-series modeling, and NLP. Optimization knowledge is a plus.
• Experience developing and deploying machine learning models in one of: AWS, Azure, or GCP, with an understanding of cloud services, architecture, and scalable solutions (examples include Sagemaker, Azure ML, Kubernetes, Airflow).
• Demonstrated experience with MLOps, including CI/CD for ML, model versioning, monitoring, and performance tracking for production environments.
• Exposure to designing, developing, and deploying agentic AI systems (such as multi-agent orchestration or automation workflows) using frameworks such as LangChain.
• Hands-on experience working with structured and unstructured datasets, including extracting and manipulating information, and comfort with best practices for data acquisition and warehousing.
• Proficiency in Excel and PowerPoint, along with excellent written and oral communication skills.
• Ability to understand and articulate requirements for both technical and non-technical audiences, collaborating across data science, engineering, and consulting teams.
• Commercial business analytics and strategic consulting experience is preferred, and exposure to one or more core sectors (life sciences, healthcare, consumer, industrials, TMT) is a strong plus.
• Strong problem-solving skills, ability to translate business needs into technical solutions, and comfort working at pace in a fast-moving, entrepreneurial environment with a high level of ownership.
• Ability to achieve results through others, with experience working in matrix, agile, and fast-growing environments, and a track record of continuous improvement.
• Legal authorization to work in the United States on a permanent basis without employer sponsorship.

Technologies

• Python, scikit-learn, TensorFlow, PyTorch, Spark, SQL, NLP, LLMs
• AWS, Azure, GCP, Sagemaker, Azure ML, Kubernetes, Airflow
• CI/CD, LangChain, MLOps
• Excel, PowerPoint

Compensation and benefits

• Expected base salary: $110,000 - $120,000 annually
• Medical, dental, vision, life and disability insurance
• 401(k) with employer contribution
• HSA contributions (where applicable)
• Paid time off
• Other firm-sponsored benefits
• This position may also be eligible for a discretionary bonus and a comprehensive benefits package

Education

• Degree in a quantitative and/or business discipline preferred, including Statistics, Computer Science, Data Science, Mathematics, Operations Research, Engineering, or Economics

Additional information

• Hybrid role aligned to U.S. offices, based in Boston, Chicago, Los Angeles, New York, or San Francisco.
• For assigned home office attendance, employees must be present Tuesday, Wednesday, and Thursday each week, plus the first Friday of each month.
• L.E.K. Consulting is unable to consider candidates requiring visa sponsorship, including H-1B, TN, F-1 (OPT/CPT/STEM), or other work authorization.
• L.E.K. Consulting is an Equal Opportunity Employer and provides reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs, practices, or observances, in accordance with applicable state and local laws.