Entry Level Data Scientist

About the job you’re considering

The Entry Level Data Scientist 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.

About The Role

Responsible for developing and implementing AI-assisted marketing analytics solutions that address customer needs using data science and machine learning. Work closely with multi-functional teams to deliver innovative solutions that drive business growth and improve customer engagement.

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.

Benefits

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• 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

Key skills/competency

• Machine Learning Algorithms
• Generative AI
• Natural Language Processing (NLP)
• Computer Vision
• Predictive Analytics
• Feature Engineering
• Data Preprocessing
• Data Pipelines
• MLOps
• Model Deployment