Journeyman Data Scientist

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 Journeyman 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.

Primary Responsibilities:

• Develop and apply statistical models and machine learning algorithms to analyze structured and unstructured data.
• Perform data exploration feature engineering and data preprocessing to support analytics and model development.
• Support development and validation of predictive and descriptive analytics models.
• Collaborate with data engineers to ensure availability and quality of data for analytics workflows.
• Assist in integrating models into production environments through APIs and DevSecOps pipelines.
• Develop visualizations dashboards and reports to communicate analytical findings.
• Support evaluation of model performance including accuracy bias and reliability.
• Assist in implementation of model monitoring and continuous improvement processes.
• 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 cross-functional teams including AI/ML engineers software developers and domain stakeholders.
• Ensure responsible AI practices including bias detection explainability and performance monitoring.
• Translate complex analytical findings into actionable insights for technical and executive stakeholders.
• Develop and maintain documentation evaluation metrics and model performance dashboards.
• Document analytical methodologies models and results.
• Participate in SAFe ceremonies including sprint planning backlog refinement sprint reviews and retrospectives.

Basic Qualifications:

• Active Secret clearance.
• Bachelors degree in Data Science Computer Science Mathematics Statistics Engineering or related technical discipline and 48 years of relevant experience OR Masters degree in a related field and 26 years of relevant experience.
• Minimum of 4 years of experience in data science data engineering or a related field.
• Experience applying statistical analysis and machine learning techniques.
• Experience using programming languages such as Python SQL R or similar analytical programming languages.
• Experience working with data analysis and ML libraries (e.g. Pandas Scikit-learn or similar).
• Experience performing data exploration feature engineering and model validation.
• Proven experience in designing and developing predictive models and data-driven analytical frameworks.
• 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 Top Secret clearance.
• Experience operating within Agile or SAFe frameworks supporting enterprise systems.
• Experience with data engineering tools and platforms such as Hadoop Spark or similar.
• Experience with data visualization tools such as Tableau or Power BI.
• Experience developing and deploying machine learning and statistical models in enterprise environments.
• Experience supporting analytics across multi-enclave DoD environments.
• Experience working with cloud-based data and AI/ML platforms (AWS Azure or GCP).
• Experience with machine learning frameworks (e.g. PyTorch TensorFlow Scikit-learn or equivalent).
• Familiarity with LLMs generative AI or NLP techniques.
• Experience supporting AI/ML model deployment and operationalization.
• Experience with data catalog management and data sharing agreements.
• Experience implementing model monitoring drift detection and continuous validation frameworks.
• Experience with data visualization tools (e.g. Tableau Power BI).

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

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job education experience knowledge skills and abilities as well as internal equity alignment with market data applicable bargaining agreement (if any) or other law.