Senior Data Scientist

Capgemini Government Solutions (CGS) LLC is seeking a highly motivated Senior Data Scientist to lead the development and deployment of models and methodologies that enable pattern analysis, predictive modeling, intelligent automation, and AI/ML solutions. The successful candidate will have the opportunity to conceive and deliver innovative data science solutions to the U.S. Public Sector to help address critical national and global challenges such as health, climate change, and national security.

This individual will join our Data and AI practice in the DC Metro Area. As a part of the rapidly expanding CGS Data and AI practice, the candidate will also help our clients develop, deploy, and modernize their data science products and ecosystems.

At Capgemini, we are committed to our staff's professional development and offer a wide range of training and educational resources. In addition to our internal learning sites, we partnered with Coursera and Degreed to provide our staff with the latest courses from academic institutions around the world. We provide education expense reimbursements as well as sponsor seminars, conferences, and certifications. Our practice leaders work with every team member to chart appropriate career paths and goals to ensure that we stay innovative and transformative, maximizing our ability to scale up solutions, keep up with the cutting edge, and bring the art of what's possible to the Federal Government.

• Provide subject matter expertise in data science, machine learning, and artificial intelligence to an entrepreneurial and high‑performing team.
• Drive data science and AI/ML‑related solutions based on evaluation of requirements, resources, and alternatives.
• Lead exploratory data analysis to evaluate data pipelines and construct data stores (structured, semi‑structured, and unstructured) as needed to feed frameworks/models.
• Manage development of custom algorithms, frameworks, and models or leverage available tools, libraries, and applications to solve complex problems.
• Oversee deployment of data science and AI/ML solutions and develop methodologies to scale up.
• Coordinate internal and external stakeholders for pattern analysis, predictive modeling, intelligent automation, GenAI, OCR, NLP, fraud detection, and other business cases for using data science, machine learning, and artificial intelligence.
• Present and articulate findings and solutions to clients and team members.
• Maintain knowledge of advances in data science across industry and academia.
• Contribute to the overall growth of the Data and AI practice.

• U.S. Citizenship is required.
• Eligible to obtain and maintain a Government Security Clearance.
• Be at client site full time in Washington, DC.
• Bachelor's degree or higher in data science, statistics, computer science, economics, mathematics, information systems, or a similar field is preferred.
• Minimum of ten (10) years of professional experience (relevant advanced degrees may substitute equivalent number of years) with data science, AI/ML, or deep learning delivery responsibilities such as:
  • Managing teams to deliver work products that comply with quality, time, and technical targets.
  • Coordinating and influencing stakeholders, managing communications, and managing client expectations.
  • Designing and developing data models and algorithms for multi‑objective optimization and decision making.
  • Building and deploying predictive and prescriptive analytics.
  • Conducting hypothesis testing, statistical and probability analyses.
  • Applying appropriate methods to describe statistical relationships between variables.
  • Performing multiple correspondence analysis (MCA), principal component analysis (PCA), and association rule mining.
• Experience using tools such as Databricks;
  Azure Machine Learning and AI Services; AWS Sage Maker and Bedrock.
• Experience programming in languages such as Python, R, Scala, SQL, JavaScript, C/C++, and Java.
• Experience using libraries and frameworks such as Tensor Flow, PyTorch, mpi4py, Spark ML/MLlib, Jupyter, h2o, Keras, or Mir.
• Experience collecting and managing large data sets in cloud‑based databases, data lakes, and data…