Associate AI - Data Scientist / ML Engineer (Azure)

Capgemini • Nashville, TN

52d • Onsite

About The Position

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.

The Data Scientist / ML Engineer will demonstrate strong expertise in machine learning algorithms such as Linear and Logistic Regression, Clustering/Segmentation, Decision Trees, Random Forest, Gradient Boosting (GBM), Deep Neural Networks (DNN), Naive Bayes, Support Vector Machines (SVM), and related techniques. This role requires the ability to lead technical initiatives, collaborate with cross-functional teams, manage projects, and engage effectively with customers to deliver scalable, cloud-based AI solutions.

Requirements

• Demonstrate strong expertise in machine learning algorithms such as Linear and Logistic Regression, Clustering/Segmentation, Decision Trees, Random Forest, Gradient Boosting (GBM), Deep Neural Networks (DNN), Naive Bayes, Support Vector Machines (SVM), and related techniques.
• Ability to lead technical initiatives.
• Ability to collaborate with cross-functional teams.
• Ability to manage projects.
• Ability to engage effectively with customers to deliver scalable, cloud-based AI solutions.
• Design, implement, and optimize machine learning models across supervised, unsupervised, and reinforcement learning paradigms.
• Develop solutions involving Natural Language Processing (NLP), computer vision, recommendation systems, and predictive analytics.
• Perform feature engineering, data preprocessing, model selection, and hyperparameter tuning.
• Experiment with and evaluate novel algorithms and advanced ML techniques to solve complex business problems.
• Build, train, and deploy models using Azure Machine Learning and associated SDKs.
• Design and maintain scalable data and ML pipelines using Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake Storage (ADLS).
• Deploy and operationalize models using Azure Kubernetes Service (AKS), Azure Container Instances, or Azure Functions.
• Implement CI/CD and MLOps best practices using Azure DevOps or GitHub Actions for model versioning, testing, and deployment.
• Monitor model performance, data drift, and model health; retrain models as required to ensure continued accuracy and reliability.
• Optimize inference performance, cost, and resource utilization in Azure environments.
• Collaborate closely with Data Engineers to ingest, transform, and manage large-scale structured and unstructured datasets.
• Ensure high standards of data quality, consistency, security, and governance in compliance with enterprise and regulatory requirements.
• Work with software engineers, data scientists, and product managers to seamlessly integrate ML solutions into business applications and platforms.
• Stay current with emerging trends in machine learning, AI, and Azure cloud technologies.
• Evaluate new tools, frameworks, and libraries to continuously enhance solution quality and performance.
• Mentor junior engineers and data scientists, promoting best practices in ML development, cloud architecture, and MLOps.

Responsibilities

• Responsible for developing and implementing AI-assisted marketing and business analytics solutions using data science and machine learning on Microsoft Azure.
• Partner closely with stakeholders across engineering, product, and business teams to deliver innovative, secure, and scalable solutions that drive business growth and improve customer engagement.
• Design, implement, and optimize machine learning models across supervised, unsupervised, and reinforcement learning paradigms.
• Develop solutions involving Natural Language Processing (NLP), computer vision, recommendation systems, and predictive analytics.
• Perform feature engineering, data preprocessing, model selection, and hyperparameter tuning.
• Experiment with and evaluate novel algorithms and advanced ML techniques to solve complex business problems.
• Build, train, and deploy models using Azure Machine Learning and associated SDKs.
• Design and maintain scalable data and ML pipelines using Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake Storage (ADLS).
• Deploy and operationalize models using Azure Kubernetes Service (AKS), Azure Container Instances, or Azure Functions.
• Implement CI/CD and MLOps best practices using Azure DevOps or GitHub Actions for model versioning, testing, and deployment.
• Monitor model performance, data drift, and model health; retrain models as required to ensure continued accuracy and reliability.
• Optimize inference performance, cost, and resource utilization in Azure environments.
• Collaborate closely with Data Engineers to ingest, transform, and manage large-scale structured and unstructured datasets.
• Ensure high standards of data quality, consistency, security, and governance in compliance with enterprise and regulatory requirements.
• Work with software engineers, data scientists, and product managers to seamlessly integrate ML solutions into business applications and platforms.
• Stay current with emerging trends in machine learning, AI, and Azure cloud technologies.
• Evaluate new tools, frameworks, and libraries to continuously enhance solution quality and performance.
• Mentor junior engineers and data scientists, promoting best practices in ML development, cloud architecture, and MLOps.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees