Data Scientist

What You'll Do

• Apply statistical analysis, machine learning, and artificial intelligence techniques to solve complex business and mission challenges.
• Analyze large datasets to identify trends, patterns, anomalies, and operational insights.
• Develop predictive, prescriptive, and advanced analytical solutions.
• Design, build, evaluate, and refine machine learning models.
• Develop data visualizations, dashboards, and analytical products that communicate findings effectively.
• Transform raw data into actionable recommendations for stakeholders.
• Collaborate with customers to understand mission needs and operational requirements.
• Support enterprise analytics initiatives and decision-support capabilities.
• Participate in model validation, testing, and quality assurance activities.
• Provide technical leadership and mentoring within project teams.
• Participate in Agile development activities and cross-functional collaboration.

Required Qualifications

• Education: Master's Degree or Ph.D. in Data Science, Statistics, Applied Mathematics, Computer Science, Operations Research, Artificial Intelligence, or a related quantitative discipline.
• Experience: Six (6) years of experience in applied research, big data analytics, statistics, data science, computer science, operations research, or related quantitative disciplines.
• Experience: Three (3) years of direct machine learning experience.
• Experience: Experience working with large-scale structured and complex datasets.
• Experience: Experience developing predictive and prescriptive analytics solutions.
• Experience: Experience designing and implementing statistical and machine learning models.
• Experience: Experience supporting enterprise analytics and decision-support initiatives.

Knowledge & Skills

• Expertise: Expertise in data mining, statistical analysis, machine learning, artificial intelligence, and data visualization.
• Skills: Strong analytical, quantitative, and problem-solving skills.
• Communication: Ability to communicate analytical concepts and findings to technical and non-technical audiences.
• Leadership: Ability to independently lead analytical efforts from concept through implementation.

Preferred Qualifications

• Experience: Experience supporting CBP, DHS, defense, intelligence, law enforcement, financial crimes, or trade-related programs.
• Experience: Experience with trade analytics, fraud detection, risk scoring, compliance monitoring, or investigative analytics.
• Experience: Experience developing production-ready machine learning solutions.
• Knowledge: Familiarity with Natural Language Processing (NLP), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Explainable AI, and MLOps practices.
• Experience: Experience with cloud-based analytics and enterprise data platforms.

Preferred Technical Skills

• Languages: Python, SQL, R.
• Tools: Spark, Databricks, TensorFlow, PyTorch, Scikit-Learn.
• Visualization Tools: Power BI, Tableau.
• Version Control: Git.
• Methodologies: Agile Methodologies.

Security Requirements

• Clearance: Active Top Secret security clearance required.
• Access: Ability to obtain and maintain access to DHS and CBP systems and facilities.

Benefits

• Employee Ownership (ESOP).
• Remote Work Flexibility.
• Meaningful National Security Mission.
• Exposure to Advanced Analytics, AI, and Big Data Technologies.
• Career Growth and Professional Development.
• Collaborative and Innovative Culture.
• Competitive Compensation and Benefits.