AI/ML Data Scientist

This is a Fully Remote Job

About Our Client:

The organization operates in the defense and government technology sector, focusing on providing advanced data analytics and artificial intelligence/machine learning (AI/ML) solutions to support mission-critical operations. It addresses challenges related to leveraging data science and AI technologies to meet the operational and business needs of a federal maritime service, enhancing decision-making and operational efficiency.

About the Opportunity:

The AI/ML DATA SCIENTIST role contributes to the development and implementation of AI and data analytics solutions that support mission and business functions. This position aids in discovering use cases, assessing data readiness, building prototypes, and piloting models, working closely with multidisciplinary teams. The role is essential in advancing AI/ML applications that improve operational outcomes and decision advantages.

Responsibilities:

• Support design, development, testing, and evaluation of AI/ML solutions for mission and business operations.
• Assist in predictive, classification, anomaly detection, natural language processing, generative AI, and other analytical solution development.
• Contribute to training, tuning, validation, and documentation of machine learning models.
• Support AI-enabled MVPs, technical demonstrations, automation pilots, and rapid experimentation.
• Research and assess commercial, government, and open-source AI/ML models and tools.
• Conduct exploratory data analysis with structured and unstructured datasets.
• Identify trends, patterns, anomalies, and insights to aid decision-making.
• Assist in developing model baselines, performance measures, acceptance criteria, and testing methods.
• Evaluate model accuracy, reliability, limitations, and operational suitability.
• Develop dashboards, visualizations, and analytical summaries.
• Follow established data science methods and team best practices.
• Support data readiness assessments regarding availability, quality, completeness, lineage, ownership, and accessibility.
• Clean, normalize, transform, and prepare data for AI/ML analysis.
• Diagnose data-quality issues and document corrective actions.
• Assist in developing data pipelines, ETL processes, and reusable datasets.
• Help integrate data from various systems and platforms.
• Collaborate with engineers to transition prototypes to scalable solutions.
• Support automation assessments and pilot evaluations.
• Assist in identifying AI/ML opportunities for workflow automation and digital transformation.
• Support integration of AI/ML with enterprise platforms and tools.
• Participate in business process analyses to reduce manual effort.
• Support intelligent document processing and AI-assisted workflow improvements.
• Aid mission modeling and simulation efforts for operational evaluation.
• Assist in scenario planning, forecasting, experimentation, and trade-space analysis.
• Translate analytical outputs into clear findings for diverse audiences.
• Support data-driven decision-making aligning operational needs with analytics.
• Collaborate on AI governance, security, privacy, and responsible AI use.
• Document assumptions, methodologies, risks, and lessons learned.
• Support authorization documentation and reviews.
• Engage in Agile development activities and stakeholder collaboration.
• Prepare technical documentation and stakeholder presentations.
• Measure user adoption, operational impact, and efficiency gains.

Requirements:

• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Artificial Intelligence, Engineering, Information Systems, Operations Research, or related field.
• 0–2 years of experience in data science, machine learning, AI, or advanced analytics.
• Foundational experience with machine learning model development or evaluation.
• Working knowledge of Python, SQL, Scikit-Learn, TensorFlow and/or PyTorch, Hugging Face or similar frameworks.
• Experience with predictive analytics, statistical analysis, data mining, and model evaluation.
• Experience with structured and/or unstructured datasets.
• Exposure to Generative AI, Large Language Models, or prompt engineering.
• Exposure to Retrieval Augmented Generation concepts or architectures.
• Familiarity with cloud and data platforms such as AWS, Azure, GovCloud, Databricks, Apache Spark, Hadoop, Kafka, Airflow, or AWS Glue.
• Ability to support AI/ML integration with APIs, …