Data Scientist

CapgeminiBridgewater, NJ
33dHybrid

About The Position

Are you ready to shape the future of digital transformation through AI and machine learning? We’re looking for a Data Scientist who thrives on innovation and wants to make an impact at scale. In this role, you’ll lead high-impact projects that drive personalization, automation, and smarter decision-making across our digital products. You’ll collaborate with top-tier professionals in a fast-paced, inclusive environment, working with cutting-edge technologies like Large Language Models (LLMs), Generative AI, and Knowledge Graphs. You’ll work on projects that truly matter, driving AI/ML adoption across a global organization. You’ll have the chance to innovate, learn, and grow alongside industry experts while contributing to a culture that values diversity, creativity, and continuous improvement. Hybrid in Philadelphia, PA – relocation available for the right candidate.

Requirements

  • 7+ years of experience in Data Science, Machine Learning, or related fields.
  • Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
  • Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring.
  • Proficiency in cloud platforms (GCP/AWS) and scalable data engineering.
  • Strong understanding of probability theory, statistics, and experimental design (A/B Testing).
  • Experience with collaborative software engineering practices (Agile, DevOps).
  • Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or related field.

Nice To Haves

  • Experience with Knowledge Graphs and their integration into AI/ML pipelines.
  • Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies.
  • Background in Retail and Personalization Web Technologies.
  • Understanding of digital ecosystems and data-driven decision-making.
  • Proficiency in BI tools and data visualization.

Responsibilities

  • Develop and optimize predictive and prescriptive models to extract insights and enhance decision-making.
  • Apply deep learning and neural network techniques for customer classification, segmentation, and personalization.
  • Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production.
  • Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement.
  • Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations.
  • Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred).
  • Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently and implement CI/CD workflows to automate model training, deployment, and monitoring.
  • Collaborate in an Agile/DevOps environment, promoting a data-centric culture and clearly communicating complex methodologies and insights to technical and non-technical audiences.

Benefits

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility
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