Senior Data Scientist

Leidos; Alexandria (VA); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading defense contractor is seeking a Senior Data Scientist in Virginia to enhance enterprise data capabilities. This role involves developing predictive models, collaborating with engineering teams, and ensuring the accuracy of analytical outputs. Ideal candidates will have over 8 years of experience and a strong background in data science and machine learning. The position also requires an active Top Secret clearance. Engage in a fast-paced, mission-driven environment that values innovation and problem-solving.

Qualifications

• Minimum of 8 years of experience in data science or engineering.
• Experience with data governance frameworks.
• Knowledge of machine learning algorithms.

Responsibilities

• Lead extraction of insights from operational data.
• Develop advanced statistical models and predictive analytics.
• Collaborate with functional teams to ensure accuracy of outputs.

Skills

Python

R

SQL

Data analysis

Machine learning

Statistical modeling

Data visualization

Problem-solving

Education

Bachelor’s degree in Data Science or related field

Master’s degree in related field

Tools

Hadoop

Spark

AWS

Azure

Google Cloud

Tableau

Power BI

Job description

Description

This Department of War enterprise data and analytics program delivers mission-critical capabilities that enable leaders across the Department to make faster, better-informed decisions using trusted data at scale. Leidos Digital Modernization sector is seeking an experienced Senior Data Scientist to support the delivery, enhancement, and adoption of enterprise data and analytics products used across multiple DoD organizations.

In this role, you will work alongside government partners, engineers, and other industry teammates to translate operational and strategic requirements into scalable, production-ready solutions. You will contribute directly to product planning, execution, and continuous improvement—helping ensure capabilities are delivered efficiently, aligned to mission priorities, and positioned for sustained success.

This position offers the opportunity to work on a high-visibility, enterprise program at the intersection of data, analytics, and emerging AI technologies. Ideal candidates are motivated by mission impact, comfortable operating in complex stakeholder environments, and interested in building deep domain expertise while delivering capabilities with real-world national security outcomes.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Primary Responsibilities

• Lead efforts to extract insights from operational, service, and performance data to identify opportunities for improvement.
• Lead development and deployment of advanced statistical models, machine learning algorithms, and predictive analytics solutions.
• Design and develop predictive models and data-driven analytical frameworks that optimize processes and support informed decision-making.
• Build models that forecast future demands, highlight operational and service-related risks, and detect performance anomalies in real time.
• Collaborate with engineering and functional teams to ensure analytical outputs are accurate, actionable, and aligned with mission objectives.
• Design experiments, feature engineering strategies, and model validation frameworks to support enterprise analytics objectives.
• Collaborate with data engineering teams to ensure scalable data pipelines supporting model training and inference.
• Integrate models into DevSecOps pipelines for automated testing, validation, and production deployment.
• Develop and maintain documentation, evaluation metrics, and model performance dashboards.
• Ensure responsible AI practices including bias detection, explainability, and performance monitoring.
• Participate in PI Planning, backlog refinement, sprint reviews, and Inspect & Adapt events to align analytics priorities with Program Increment (PI) objectives.
• Translate complex analytical findings into actionable insights for technical and executive stakeholders.
• Establish modeling standards, peer review processes, and analytical quality governance frameworks.
• Foster a collaborative, innovative, and mission-focused analytics culture within the organization.

Basic Qualifications

• Active Top Secret (TS) clearance with SCI eligibility.
• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or related technical discipline and 8–12 years of relevant experience OR Master’s degree in a related field and 6–10 years of relevant experience.
• Minimum of 8 years of experience in data science, data engineering, or a related field.
• Strong proficiency in programming languages such as Python, R, SQL or similar analytical programming languages.
• Experience with data engineering tools and platforms, such as Hadoop, Spark, or similar.
• Experience developing and deploying machine learning and statistical models in enterprise environments.
• Proven experience in designing and developing predictive models and data-driven analytical frameworks.
• Experience performing data exploration, feature engineering, model validation, and performance tuning.
• Knowledge of data security policies, including data encryption and access controls.
• Experience with data governance frameworks and compliance enforcement.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Active TS/SCI clearance.
• Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.
• Experience supporting analytics initiatives across NIPRNet, SIPRNet, and JWICS environments.
• Experience operationalizing AI/ML models in cloud-native environments (AWS, Azure, or GCP).
• Knowledge of machine learning algorithms and frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent.
• Experience implementing model monitoring, drift detection, and continuous validation frameworks.
• Experience supporting enterprise data, AI/ML, or digital modernization programs within DoD environments.
• Experience with cloud-based data platforms and tools, such as AWS, Azure, or Google Cloud.
• Experience with data visualization tools, such as Tableau or Power BI.
• Experience with data catalog management and data sharing agreements.
• Strong project management skills and experience leading cross-functional teams.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.