Staff Data Scientist

NAVA Software solutions is looking for a Staff Data Scientist.

Details:

Staff Data Scientist Location:

Spring TX -

Hybrid Duration:

Full time Role Overview A highly skilled ML/AI Engineer or Data Scientist specializing in agentic AI possesses deep expertise in architecting and developing end to end intelligent solutions using AI agents, multi agent workflows, and modern agentic platforms.

Core Technical Skills Agentic AI & LLMs:

Proficient in large language models (LLMs), retrieval augmented generation (RAG), vector databases, and orchestration frameworks to design autonomous, context aware systems that reason, plan, and act. Skilled in prompt engineering, model fine tuning, and integrating emerging AI capabilities - such as tools, function calling, memory, and real time inference - into robust, production grade architectures that drive automation and intelligent workflow optimization.

Traditional ML:

Solid foundation in classical machine learning algorithms including regression, classification, clustering, and ensemble methods (e.g., Random Forest, XGBoost). Able to select, train, and evaluate the right model for structured data problems, applying feature engineering, cross validation, and hyperparameter tuning while understanding the trade offs between traditional approaches and deep learning solutions.

DevOps & MLOps:

Proficient in CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms (Databricks, AWS, Google Cloud Platform, Azure). Experienced with infrastructure as code, automated testing, and deployment strategies such as blue green and canary releases. Skilled in MLOps tooling - including experiment tracking (MLflow, Weights & Biases), model registries, and observability stacks - to ensure reliable, scalable, and auditable delivery of AI systems from development to production.

Experience Requirements Overall Experience:

7 10 years of hands on experience in machine learning, AI engineering, or data science, with a proven track record of delivering end to end AI solutions in production environments.

Agentic & GenAI Experience:

2 3 years of focused experience working with LLMs, agentic frameworks, and generative AI technologies, including real world deployment of RAG pipelines or multi agent systems.

Leadership & Collaboration Team Leadership:

Demonstrated experience leading and mentoring cross functional AI/ML teams of 3 5 engineers, setting technical direction, conducting code reviews, and driving best practices across the team.

Stakeholder Management:

Ability to communicate complex AI concepts clearly to non technical stakeholders, align on priorities, and present findings and recommendations to senior leadership.

Project Ownership:

Proven ability to own the full project lifecycle - from scoping and architecture through to deployment and iteration - while managing timelines, risks, and dependencies in an agile environment.