Lead Data Scientist

The Mitre Corporation•New Bedford, MA

8d•$155,200 - $232,800•Onsite

About The Position

MITRE is seeking a Lead Data Scientist for its Acquisition Affordability and Business Analytics Department within the MITRE Technology and Engineering Acquisition Division. The department partners across MITRE and with government sponsors to address complex mission and business challenges through advanced analytics, economic modeling, and decision support. Its work includes cost estimation and analysis, investment economics and decision analysis, and strategic business and financial analytics. The position supports business analytics and data science capabilities for internal and external sponsors. The Lead Data Scientist engages with sponsors and multidisciplinary teams to define analytic problems, prioritize work, and report findings that support strategic and operational decisions. The role spans the analytic lifecycle: sourcing, integrating, and validating complex datasets; exploring and cleaning structured and unstructured data; applying statistical methods, predictive models, and other analytic techniques; interpreting findings in policy, regulatory, budgetary, political, and operational contexts; and translating technical work into recommendations for stakeholders. The role also develops analytic tools, dashboards, and reusable capabilities, and presents results in reports, presentations, and in-person briefings. Beyond core data science, work may include life-cycle cost estimating, tradeoff and affordability analyses, decision analysis, portfolio investment analysis, business case analysis, and business intelligence and performance analytics. The position operates in a dynamic, collaborative environment involving multiple projects and complex, ambiguous problems. The Lead Data Scientist works independently with minimal guidance, engages directly with sponsors, leads small teams or projects, and trains or assists junior staff. The position requires at least four days per week onsite and requires the ability to obtain and maintain a Top Secret U.S. government security clearance within one year of hire.

Requirements

Typically requires at least 8 years of related experience with a bachelor’s degree, 6 years with a master’s degree, or 3 years with a Ph.D., or an equivalent combination of related education and work experience.
Bachelor’s degree in Operations Research, Mathematics, Statistics, Economics, Finance, Data Analytics, Data Science, Systems Engineering, or another engineering or quantitative analysis field.
Expertise in Python or R for data science and modeling.
Expertise in code environment management and versioning, such as Git and IDEs.
Experience programmatically accessing and integrating structured and unstructured data from enterprise databases, APIs, and cloud-based data platforms.
Expertise in data processing, exploratory data analysis, and working with structured and unstructured data sources.
Expertise in machine learning and natural language processing, including model tuning, computer vision, time-series analysis, and related packages such as scikit-learn.
Ability to independently identify appropriate statistical and/or machine-learning methods for a given task.
Ability to use AI responsibly to augment work, including exercising judgment about when to validate and tune LLM outputs.
Expertise in selecting visualizations to communicate findings using tools and approaches such as Power BI, Tableau, Qlik, Leaflet, R Shiny, Plotly, Seaborn, ggplot, or other packages.
Expertise in statistical methods, including regression, forecasting, and hypothesis testing.
Excellent written and verbal communication skills.
Expertise with Microsoft Office, especially Excel, Word, and PowerPoint.
Must be eligible to obtain and maintain a Top Secret U.S. government-issued security clearance; candidates must be U.S. citizens to be considered for a security clearance.
Must work onsite at least four days per week.

Nice To Haves

Master’s degree in Economics, Mathematics, Statistics, Finance, Business, Operations Research, Data Analytics, Data Science, Systems Engineering, or another engineering field.
Expertise in additional programming languages, including SQL or Java.
Experience with software engineering best practices and agile DevOps software development processes.
Experience with econometric or economic modeling and analysis.
Working knowledge of federal budgeting and spending mechanics, processes, and data.
Knowledge of Planning, Programming, Budgeting, and Execution (PPBE) and OMB Circular A-11.
Knowledge of acquisition reform and PPBE reform initiatives.
Knowledge of Federal Acquisition Regulations.
Knowledge of Capital Planning and Investment Control (CPIC).
Experience with federal spending data, including USASpending.gov, SAM.gov, or FPDS-NG.
Experience in investment modeling and analysis, cost-benefit analysis, large-dataset analysis, policy and investment analysis, economic analysis supporting regulatory policy, pre- and post-implementation analysis, forecasting, and applied research.
Expertise and experience in data engineering and cloud computing, such as Amazon Web Services or Microsoft Azure.
Cost-estimating experience, including developing Independent Government Cost Estimates (IGCEs) or using parametric cost-estimating tools such as PRICE or SEER SEM.
Source selection cost evaluation experience.
ICEAA certification or Defense Acquisition Workforce Initiative Act (DAWIA) certification.
An active Top Secret security clearance.

Responsibilities

Identify sources and gather quantitative and qualitative data to support decisions affecting MITRE and its government sponsors.
Select and apply analytical methods, including exploratory data analysis, time-series analysis, linear regression, text analysis, and machine learning.
Draw conclusions from analyses and clearly communicate findings in writing and verbally.
Lead presentations of findings to senior-level stakeholders.
Recommend and develop data visualizations that improve the presentation of complex datasets and analyses.
Translate unstructured data and nontraditional information sources into business insights.
Explore sponsor environments for cross-government challenges and identify potential best practices.
Develop investment, economic, and decision analyses, including business case analyses, cost/benefit analyses, analyses of alternatives, and portfolio analyses.
Develop strategic business and financial analyses, including economic studies, cost-recovery strategies, budget development and planning, and affordability analysis.
Assess government and industry cost estimates and economic analyses.
Work independently with minimal guidance and proactively identify, analyze, and communicate significant issues, findings, risks, and opportunities to leadership and stakeholders.
Lead small teams on tasks or small projects and train or assist junior staff.
Source, integrate, and validate complex datasets; explore and clean structured and unstructured data; and develop analytic tools, dashboards, or reusable capabilities.
Deliver findings through written reports, presentations, and in-person briefings to technical and non-technical audiences.