Work with and lead a team of data scientists and data engineers on defining and creating scalable AI data architecture strategy
Identify risks and constraints of AI infrastructure at scale and implement mitigations and workarounds
Create project plan, milestones and lead the team to Implement the AI data architecture strategy
Lead the design and implementation of data access controls to produce a data transformation pipeline that discovers, repairs, logs, and deploys quality data plus security policy metadata
Work with a team to design, build, train, and evaluate machine learning models
Be the liaison between executive level leadership, research team and other stakeholders across Leidos.
Communicate results and methods for solutions to internal and external stakeholders.
Work within teams of AI/ML researchers and engineers using Agile development processes
Requirements & Skills:
Bachelor’s degree in Computer Science, Data Science or related field and over 16 years of relevant experience, Masters with 14 years experience, or PhD with 10 years experience.
Experience with data architecture at scale and AI Infrastructure
Experience with data categorization, labeling and tagging
Experience with data repositories and ETL
Experience with Data Operations including applying AI for data curation
Strong Python programming fundamentals
Good understanding of machine learning algorithms, tools and platforms
Experience with AI/ML tools, such as common Python packages (e.g., scikit-learn, NumPy, Pandas)
Experience with tabular data analysis using languages such as SQL, R, and/or Python
Experience with statistical modeling and data analysis
Experience with leading research projects and project teams
Experience with planning and execution
Great communication skills, able to explain model results to a non-technical audience
Proficient in data exploration techniques and tools such as Amazon Web Services (AWS)
Experience with data visualization libraries such as Plotly, Streamlit, and matplotlib.
Experience with MLOps tools and frameworks, such as Kubeflow, MLflow, DVC, TensorBoard
Experience with building LLM and other Generative AI applications.
Willing to learn new skills and platforms to support data analytics.
Ability and willingness to obtain a Top Secret security clearance
