Task Lead-Data Science - TS​/SCI

Overview

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

LMI is seeking a Advanced Analytics Team Lead to support an Intelligence Community client. This position will be located in Washington, DC or Reston, VA.

Responsible for overseeing a team of data engineers and data scientists to modernize data pipelines and data warehouses, while delivering business analytics support through machine learning, statistical analysis, causal analysis, and modeling and simulation.

• Lead and collaborate with a team of data engineers, data scientists, data analysts, and business/functional SMEs to understand processes, define analytical requirements, and communicate results.

• Modernize and maintain data pipelines, data warehouses, and related infrastructure to ensure scalable, reliable, and efficient operations.

• Frame and scale data problems; integrate, consolidate, and analyze complex datasets for business analytics.

• Build and validate models using machine learning, simulation, causal, rule-based, and statistical methods.

• Transform data into visualizations, dashboards, and analytic narratives that support storytelling and decision-making.

• Provide timely analysis and reporting in a fast-paced, client-focused environment.

• Deliver technical and process consulting through management of standard consulting projects.

• Advise non-technical stakeholders on interpreting and applying data products, dashboards, and reports.

• Manage relationships with key stakeholders to ensure alignment of analytical solutions with organizational goals.

• Contribute to the organization’s data engineering and advanced analytics strategy, roadmap, and data governance practices.

• Oversee project timelines, deliverables, and resources, ensuring completion on time, within budget, and to quality standards.

• Stay current with advancements in data engineering, analytics, and data science; mentor junior team members across both DE and DS disciplines, providing technical guidance to build overall team capability.

Education:

• Bachelor’s degree in data science, mathematics, statistics, economics, computer science, engineering, or a related quantitative discipline is required.
• Advanced degree (master’s or Ph.D.) in a relevant field is preferred.

Experience:

• 5-10 years of relevant experience, with at least 2 years leading data engineering or data science teams as a technical lead or task lead.
• Proven track record of managing and delivering complex data pipelines and analytical projects.
• Hands‑on experience developing with Python and SQL for data pipelines, data integration, and analytics.

Technical

Skills:

• Proficiency in Python and SQL is required.

• Strong working knowledge of relational databases; preferred experience includes database optimization, schema design (e.g., star/snowflake), and linking analytic/visualization products to database connections.

• Experience with ETL/ELT processes, pipeline development, and data integration methods.

• Familiarity with data science libraries in Python.

• Experience building data visualizations, dashboards, and lightweight applications to communicate findings and drive business impact.

• Experience displaying analytical results using platforms such as Tableau, Streamlit, Qlik, Power BI, RShiny, Plotly, or D3.js. Tableau and Streamlit preferred.

• Additional experience with programming languages such as Java, R, or MATLAB is a plus.

• Familiarity with data engineering and data science methods including data transformation,…