AI ML Data Scientist
AI ML Data Scientist
Posted yesterday
SENIORITY
Senior
About the role
- Design, develop, test, and deploy AI/ML solutions supporting DOD customer mission and business operations.
- Build predictive, prescriptive, classification, anomaly detection, natural language processing (NLP), and generative AI solutions.
- Develop machine learning models that improve operational decision-making, workforce productivity, and mission effectiveness.
- Support development of AI-enabled minimum viable products (MVPs) and automation pilots. Data Science & Analytics
- Conduct exploratory data analysis, statistical modeling, and advanced analytics using structured and unstructured data.
- Identify trends, patterns, and operational insights to support DOD customer leadership decisions.
- Develop dashboards, visualizations, performance metrics, and analytical products to support enterprise transformation initiatives.
- Establish repeatable analytics methodologies and data science best practices. Data Engineering & Integration
- Develop and optimize data pipelines supporting AI/ML initiatives.
- Assist with database design, ETL processes, data cleansing, transformation, and reporting activities.
- Design reusable and scalable data models and architectures.
- Diagnose data quality issues and recommend corrective actions.
- Support integration of data from multiple DOD customer systems and repositories. Automation & Digital Transformation
- Support automation opportunity assessments, feasibility analyses, and pilot evaluations.
- Collaborate with automation engineers to integrate AI/ML capabilities into workflow automation, RPA, ServiceNow, UiPath, Power Platform, Salesforce, and Appian solutions.
- Participate in business process reengineering efforts and identify opportunities to automate manual processes through AI and advanced analytics. Mission Modeling & Decision Support
- Support mission modeling and simulation initiatives that evaluate mission execution, staffing models, operational impacts, and technology alternatives.
- Develop analytical models that assist with scenario planning, operational experimentation, and performance forecasting.
- Provide recommendations to leadership based on model outputs and analytical findings. Agile Development & Collaboration
- Participate in Agile planning, backlog refinement, sprint reviews, demonstrations, and release activities.
- Collaborate with product owners, developers, business analysts, architects, and mission stakeholders to translate use cases into AI/ML solutions.
- Support technical demonstrations, pilot evaluations, and user feedback sessions.
- Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Artificial Intelligence, Engineering, Information Systems, or related field.
- 7+ years of experience in data science, machine learning, artificial intelligence, or advanced analytics.
- Experience developing and deploying machine learning models in production environments.
- Strong proficiency with:
- Python
- SQL
- Machine Learning frameworks (Scikit-Learn, TensorFlow, PyTorch, Hugging Face, LangChain)
- Experience performing:
- Predictive analytics
- Statistical analysis
- Data mining
- Model evaluation and validation
- Experience working with large datasets and complex data environments.
- Experience developing Generative AI and Large Language Model (LLM) solutions.
- Experience with Retrieval Augmented Generation (RAG) architecture.
- Experience with Databricks, Apache Spark, Hadoop, Kafka, Airflow, or AWS Glue.
- Experience with cloud environments including AWS, Azure, or GovCloud.
- Experience integrating AI/ML capabilities into:
- UiPath
- ServiceNow
- Power Platform
- Appian
- Strong communication skills with experience briefing technical and non-technical stakeholders.
- U.S. Citizenship required.
- Active Secret clearance.
- Experience supporting DHS, DoD, or other Federal agencies. Desired Certifications
- AWS Certified Machine Learning Engineer
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