Senior Data Scientist (Chicago, IL, US)

Capgemini
Capgemini

Data Science

Chicago, IL, USA

Posted on Sep 18, 2026

Location

St. Loiuse , MO

Your Role

The Platform Engineer is a senior leadership role responsible for managing and supporting Infrastructure Intelligence and Analytics platform during offshore hours. The position oversees production operations, data pipeline reliability, infrastructure cost optimization, application development, and leadership of the offshore platform engineering team.


Key Responsibilities


Serve as the primary offshore owner for production support, incident management, and platform availability.
Monitor and maintain data pipelines, ensuring data quality, freshness, and timely availability for AI agents and analytics systems.
Independently troubleshoot and resolve infrastructure, application, and data issues with minimal escalation.
Build and manage dashboards for system health, operational monitoring, and AWS/cloud cost tracking.
Optimize AWS infrastructure usage, AI token consumption, storage, and compute costs.
Develop automation tools, scripts, small services, and integration solutions, primarily using Python.
Lead and mentor offshore engineers, establish operational standards, runbooks, and support procedures.
Collaborate with onshore platform, data engineering, and data science teams to ensure seamless operations and handoffs.
Contribute to infrastructure architecture and operational strategy.

Required Skills and Expereince


Strong AWS expertise (EC2, S3, IAM, VPC, Glue, Athena, EMR, CloudWatch, Secrets Manager).
Experience with Terraform (preferred), CloudFormation, Docker, Linux, CI/CD, and Git-based development.
Strong background in production support, monitoring, incident response, and cost optimization.
Proficiency in Python for automation, tooling, and application development.
Knowledge of data pipelines, REST APIs, cloud SDKs (boto3), testing frameworks, and software engineering best practices.
Demonstrated leadership experience with the ability to make independent technical decisions.
Preferred Qualifications
Experience with Spark, Kafka, Airflow, graph databases (Neptune/Neo4j), and AI/ML infrastructure.
Familiarity with LLM/agent deployment, observability, and telecommunications environments.
Experience developing production APIs/services using FastAPI or Flask.
Relevant AWS certifications.


Education & Experience


Bachelor's degree (or equivalent experience) in Computer Science, IT, Systems Engineering, or related field.
8+ years of platform/infrastructure engineering experience with a bachelor's degree (including 2+ years in a lead role), or 6+ years with a master's degree.