Data Scientist

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Job Description

 

Data Scientist

Location: This is a fully remote role based anywhere in the United States.

About the Job You’re Considering 

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. 

Your Role 

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. 

Your Skills and Experience 

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. 

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. 

The base compensation range for this role in the posted location is: $76,200.- $187,740/Year

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation