Data Scientist

Company Overview At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future. Department Overview At Motorola Solutions, we create technologies our customers refer to as their lifeline. Our technology platforms in communications, software, video, and services help our customers work safely and more efficiently. Whether it’s helping firefighters see through smoke, enabling police officers to see around street corners, or reliably keeping the lights on in homes and businesses worldwide, our work supports those who put their lives on the line to keep us safe. Bring your passion, potential, and talents to Motorola Solutions, and help us usher in a new era in public safety and security. Job Description 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. Core Responsibilities AI Orchestration: Design and deploy complex AI Agents and RAG pipelines that solve reasoning tasks using frameworks like LangChain or LlamaIndex . System Architecture: Build and optimize semantic search layers using Vector databases ( PG Vector ) and advanced embedding models. Data Scaling: Engineer high-performance data models and pipelines using Python (Pandas/PySpark) to process large-scale datasets for AI consumption. Performance Engineering: Optimize LLM performance through advanced prompt engineering, context window management, and strategic fine-tuning. Production Excellence: Champion Software Craftsmanship by maintaining clean codebases, robust CI/CD workflows, and comprehensive ML Observability. Qualifications Experience: Minimum of 4 years of professional experience as a Data Scientist (post-degree). Education: 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. Preferred Qualifications GenAI & Agentic Development 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. Data Engineering & Warehousing 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. Software Craftsmanship Strong commitment to writing maintainable, production-ready code. Experience implementing MLOps principles to monitor and scale models in the wild. Preferred Skills 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. Advanced Reasoning: Experience experimenting with multi-agent systems for complex, multi-step tasks. Cloud Infrastructure: Hands-on experience scaling AI workloads on AWS (EC ... (truncated, view full listing at source)