Enterprise Data Scientist

Enterprise Data Scientist

Job Category: Science

Time Type: Full time

Minimum Clearance Required to Start: None

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Local

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The Opportunity:

Join CACI's Enterprise Digital Transformation and Analytics Team to develop and deploy AI solutions and products. Our team integrates with all functional areas across operations and the business (e.g. business development, contracts, finance, accounting, human resources, and programs. We're seeking an experienced AI engineer who will leverage classical machine learning, generative AI, and innovative analytics to develop solutions that drive operational excellence, optimize business processes and find and understand predictive insights.  You will apply  your expertise, curiosity, innovation and customer centric approach to core AI development, data engineering/cloud operations, and to internal consulting. 

You will work directly with senior customers to understand the business processes and how the data is used for decision activities and pose business questions to help drive data discoveries, data design, and proof of concepts. Use an agile, analytical approach to design, develop, and evaluate descriptive and predictive models and advanced algorithms on both structured and unstructured data. Generate and test hypotheses and derive patterns, trends, and correlations. Build repeatable machine learning systems to automate predictive models. Effectively consult and communicate with senior leaders of the results of the data models.  

AI/ML Development: Lead the development of sophisticated machine learning models, statistical analysis, and GenAI solutions. This includes developing predictive models, integrating large language models (LLMs) into existing workflows, and building scalable algorithms that work effectively across structured and unstructured data sources to solve real business challenges 

Data Engineering & Cloud Operations: Design, develop, and maintain robust data pipelines and cloud infrastructure on AWS, leveraging services such as SageMaker, Glue, Redshift, Athena, Bedrock, and Knowledge Bases to ensure scalable deployments for AI models and application development.

Internal Consulting: Partner with senior stakeholders across the organization to understand business needs, present insights, and drive AI-powered initiatives.

Applicants must be local to the DMV as regular onsite integration and collaboration to Reston, VA will be required as needed.

Responsibilities:

• Design and implement sophisticated machine learning models, including advanced regression, classification, and clustering techniques
• Develop applications using Large Language Models (LLMs) and other GenAI technologies
• Create and validate statistical prediction models
• Conduct rigorous model evaluation and testing
• Lead feature engineering and algorithm optimization efforts

Data Engineering & Cloud Operations:

• Architect and maintain data pipelines using AWS services (Athena, Redshift, Glue, Lambda, DMS)
• Implement MLOps practices for model deployment and monitoring
• Design scalable data processing solutions
• Manage data quality and infrastructure reliability
• Optimize cloud resource usage and performance

Internal Consulting & Communications:

• Partner with senior executives to identify AI opportunities
• Translate technical concepts into business value propositions
• Present findings and recommendations to stakeholders
• Drive adoption of AI solutions across the organization
• Provide guidance on AI strategy and implementation
• Work independently to plan and deliver projects – from initial concept through successful implementation
• Partner effectively with technical and business teams while clearly explaining complex ideas to different audiences
• Handle multiple projects simultaneously while keeping stakeholders informed of progress

Qualifications:

Required: 

• U.S. Citizenship is required
• Bachelor's Degree or equivalent experience with 3-5 years of ML/AI experience 
• Strong expertise in machine learning algorithms and statistical modeling
• Proven experience with LLMs and advanced NLP techniques
• Proficiency in Python and key ML libraries (scikit-learn, Pandas, NLTK, Hugging Face)
• Experience with AWS cloud services and MLOps
• Excellence in technical communication and stakeholder management
• Ability to maintain confidentiality and work in time-critical environments

Desired:

• Experience develop