Entry Level - Data Scientist- Gen Ai - ML

Overview

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

About the job you’re considering
:
The Data Scientist / ML Engineer will demonstrate excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest, GBM, DNN, Naive Bayes, Support Vector Machine, etc.) to lead efforts, teams, projects, and engage with customers.

• Design, implement, and optimize machine learning models (supervised, unsupervised, and reinforcement learning).
• Work on projects involving NLP, computer vision, recommendation systems, and predictive analytics.
• Perform feature engineering, data preprocessing, and model selection.
• Collaborate with Data Engineers to acquire and preprocess large datasets.
• Build and maintain data pipelines to support model training, testing, and deployment.
• Ensure data quality, consistency, and reliability.
• Deploy ML models into production environments using CI/CD and MLOps practices.
• Monitor model performance, retrain models, and manage model versioning.
• Optimize inference performance and resource utilization.
• Stay current with emerging ML/AI technologies, frameworks, and research.
• Evaluate new algorithms, tools, and libraries to improve model performance.
• Experiment with novel approaches to solve complex business problems.
• Work with software engineers, data scientists, and product managers to integrate ML solutions into applications.
• Mentor junior engineers and share best practices in ML development and deployment.

Your Roles & Responsibilities:

• Design, implement, and optimize machine learning models (supervised, unsupervised, and reinforcement learning).
• Work on projects involving NLP, computer vision, recommendation systems, and predictive analytics.
• Perform feature engineering, data preprocessing, and model selection.
• Collaborate with Data Engineers to acquire and preprocess large datasets.
• Build and maintain data pipelines to support model training, testing, and deployment.
• Ensure data quality, consistency, and reliability.
• Deploy ML models into production environments using CI/CD and MLOps practices.
• Monitor model performance, retrain models, and manage model versioning.
• Optimize inference performance and resource utilization.
• Stay current with emerging ML/AI technologies, frameworks, and research.
• Evaluate new algorithms, tools, and libraries to improve model performance.
• Experiment with novel approaches to solve complex business problems.
• Work with software engineers, data scientists, and product managers to integrate ML solutions into applications.
• Mentor junior engineers and share best practices in ML development and deployment.

The base compensation range for this role in the posted location is:$120,000 TO $145,000.

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 such as variable incentives,…