Senior Associate Data Science/Machine Learning - Chicago - Hybrid

Publicis Groupe · Chicago · $117,000–$160,000 (stated in the posting)

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Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value.

Senior Associate Data Science - Chicago Hybrid 

As a Senior Associate Data Scientist, you will be responsible for developing and deploying machine learning models at scale. You will work closely with cross-functional teams to design, implement, and optimize data-driven solutions that drive business impact. Your expertise in ML engineering will be crucial in building robust, scalable, and efficient AI systems.

Your Impact

• Design, develop, and deploy machine learning models to solve complex business problems.
• Collaborate with data engineers, product managers, and business stakeholders to implement end-to-end ML solutions.
• Optimize and scale machine learning pipelines for performance and efficiency.
• Ensure the reliability, scalability, and maintainability of AI/ML systems in production.
• Utilize cloud-based platforms (AWS, GCP, Azure) for model training, deployment, and monitoring.
• Implement best practices in data preprocessing, feature engineering, and model evaluation.
• Stay updated with the latest advancements in ML engineering and AI technologies.

Skills & Experience

• 5+ years of experience in machine learning, data science, or AI engineering.
• Strong expertise in ML model development, deployment, and optimization.
• Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
• Experience with MLOps, CI/CD pipelines, and model monitoring.
• Hands-on experience with cloud-based ML platforms (AWS SageMaker, GCP AI Platform, Azure ML).
• Strong understanding of data engineering, data pipelines, and big data technologies.
• Excellent problem-solving and analytical skills.

Set Yourself Apart With

• Experience in building and deploying large-scale AI/ML systems.
• Knowledge of Kubernetes, Docker, and other containerization technologies.
• Expertise in time-series forecasting, NLP, or computer vision.
• Certifications in ML engineering, MLOps, or cloud platforms.

Additional information:

Salary Range: $117,000 - $160,000

The ranges shown above represent a grouping of relevant ranges currently in use at Publicis Sapient. The actual range for this position may vary based on location and the specific skills required for the role.

Benefits include:

• Access to ongoing learning and development opportunities.
• Competitive compensation and benefits package.
• Flexibility to support work-life balance.
• Comprehensive health benefits for you and your family.
• Generous paid leave and holidays.
• Wellness program and employee assistance.

As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at hiring@publicis.sapient.com

Skills & Experience

• 5+ years of experience in machine learning, data science, or AI engineering.
• Strong expertise in ML model development, deployment, and optimization.
• Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
• Experience with MLOps, CI/CD pipelines, and model monitoring.
• Hands-on experience with cloud-based ML platforms (AWS SageMaker, GCP AI Platform, Azure ML).
• Strong understanding of data engineering, data pipelines, and big data technologies.
• Excellent problem-solving and analytical skills.

Set Yourself Apart With

• Experience in building and deploying large-scale AI/ML systems.
• Knowledge of Kubernetes, Docker, and other containerization technologies.
• Expertise in time-series forecasting, NLP, or computer vision.
• Certifications in ML engineering, MLOps, or cloud platforms.

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