Analytics and Data Engineering Team Lead - TS/SCI Required | LMI · Teeming.ai
LMI
LMI is a consultancy dedicated to improving the business of government, drawing from deep expertise in advanced analytics, digital services, logistics, and management advisory services. Established as a private, not-for-profit organization in 1961, LMI is a trusted third party to federal civilian and defense agencies, free of commercial and political bias.
LMI is a consultancy dedicated to improving the business of government, drawing from deep expertise in advanced analytics, digital services, logistics, and management advisory services. Established as a private, not-for-profit organization in 1961, LMI is a trusted third party to federal civilian and defense agencies, free of commercial and political bias.
Improving government operations, logistics, readiness, and mission outcomes through technology and consulting.
Founded
1961
Industry
Government technology & consulting
Funding Track Record
Funding
Founders
What we do
Join the Team
Analytics and Data Engineering Team Lead - TS/SCI Required
On-SiteWashington, US
On-Site • Washington, US
Overview
At LMI, we’re reimagining the path from insight to outcome at The New Speed of Possible™. Combining a legacy of over 60 years of federal expertise with our innovation ecosystem, we minimize time to value and accelerate mission success. We energize the brightest minds with emerging technologies to inspire creative solutioning and push the boundaries of capability. LMI advances the pace of progress, enabling our customers to thrive while adapting to evolving mission needs.
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.
Responsibilities
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.
EducationQualifications
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. Finish
Experience building data visualizations, dashboards, and lightweight applications to communicate findings and drive business impact.
Leadership And Interpersonal Skills
Superior communication skills, both oral and written, with the ability to convey complex data engineering and data science concepts to non-technical stakeholders.
Demonstrated ability to mentor and develop junior team members across both DE and DS disciplines.
Strong stakeholder management skills, with the ability to build and maintain relationships across the organization.
Proven ability to balance technical modernization efforts with stakeholder-facing analytics delivery .
Ability to work in a fast-paced, solutions-oriented environment.
Strong analytical and problem-solving skills with a focus on practical outcomes.
Detail-oriented with a commitment to delivering high-quality work.
This position requires an active
TS/SCI security clearance with polygraph
. Applicants with
TS/SCI who are eligible for polygraph are encouraged to apply and will be sponsored for upgrade.
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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.
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, feature engineering, predictive analytics, and (preferred) unstructured text/NLP.
Ability to work both independently and as part of a collaborative team.