Data Scientist

Motorola Solutions•Schaumburg, IL

1d•Onsite

About The Position

We are seeking a high-caliber Data Scientist to join our team, leveraging large-scale datasets to drive mission-critical business strategy. Unlike traditional analytical roles, this position requires a practitioner who can navigate the entire lifecycle of a data project, from raw data extraction to the deployment of production-grade machine learning models. The ideal candidate possesses a deep mastery of statistical theory and the engineering rigor required to solve complex, real-world problems for both technical and executive audiences.

Requirements

Minimum of 4+ years of professional experience as a Data Scientist (post-degree).
Bachelor’s or Master’s in a quantitative discipline (Computer Science, Statistics, Mathematics, Physics, or a related field).
Legal authorization to work in the U.S. indefinitely is required.
Employer work permit sponsorship (H-1B, OPT, etc.) is NOT available for this position now or in the future.

Nice To Haves

2+ years of hands-on experience building and deploying AI-driven applications.
Deep understanding of Transformer architectures (Gemini, GPT, Claude).
Proven expertise in building Semantic Search layers and Google Indexing.
Expertise in Big Data processing at scale (Python/PySpark or Scala).
Professional-grade experience with Snowflake or Redshift.
Mastery of Advanced SQL and dimensional data modeling for low-latency consumption.
Strong commitment to writing maintainable, production-ready code.
Experience implementing MLOps principles to monitor and scale models in the wild.
Experience with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP).
Familiarity with version control (Git) and CI/CD for machine learning.
Excellent communication skills with a proven track record of influencing non-technical leadership.
Experience experimenting with multi-agent systems for complex, multi-step tasks.
Hands-on experience scaling AI workloads on AWS (EC2, EKS, Lambda).
Direct experience leveraging Google Gemini for multimodal or long-context applications.

Responsibilities

Design and deploy complex AI Agents and RAG pipelines that solve reasoning tasks using frameworks like LangChain or LlamaIndex.
Build and optimize semantic search layers using Vector databases (PG Vector) and advanced embedding models.
Engineer high-performance data models and pipelines using Python (Pandas/PySpark) to process large-scale datasets for AI consumption.
Optimize LLM performance through advanced prompt engineering, context window management, and strategic fine-tuning.
Champion "Software Craftsmanship" by maintaining clean codebases, robust CI/CD workflows, and comprehensive ML Observability.