Business Research Analyst

As a Research Analyst, you'll collaborate with experts to develop cutting-edge ML and Gen AI/LLM solutions for business needs. You'll drive product pilots, demonstrating innovative thinking and customer focus. You'll coordinate between science and software teams, optimizing solutions. The role requires thriving in ambiguous, fast-paced environments and working independently with ML models. You are expected to be an Expert in classical ML, generative AI, prompt engineering, and deployment optimization. Capable of building scalable and production-ready AI systems. Provide mentorship and guidance to junior members in the team. Engage in cross-functional collaboration and drive measurable business impact Key job responsibilities • Collaborate with seasoned Applied Scientists and propose best in class ML solutions for business requirements • Dive deep to drive product pilots, demonstrate think big and customer obsession LPs to steer the product roadmap • Build scalable solutions in partnership with Applied Scientists by developing technical intuition to write high quality code and develop state of the art ML models utilizing most recent research breakthroughs in academia and industry • Coordinate design efforts between Sciences and Software teams to deliver optimized solutions • Ability to thrive in an ambiguous, uncertain and fast moving ML usecase developments. • * Lead the design and deployment of hybrid ML/LLM systems (e.g., RAG pipelines, fine-tuned models) * Conduct thorough ML experimentation and make ML model and architecture design choices. * Conduct hyperparameter tuning, prompt optimization, and performance monitoring at scale * Work on ML Ops to implement reproducible pipelines and experiment tracking * Translate ambiguous business problems into AI/ML solutions • Mentor Junior Research Analyst (RAs) and contribute to RA hiring About the team Retail Business Services Technology (RBS Tech) team develops the systems and science to accelerate Amazon’s flywheel. The team drives three core themes: 1) Find and Fix all customer and selling partner experience (CX and SPX) defects using technology, 2) Generate comprehensive insights for brand growth opportunities, and 3) Completely automate Stores tasks. Our vision for MLOE is to achieve ML operational excellence across Amazon through continuous innovation, scalable infrastructure, and a data-driven approach to optimize value, efficiency, and reliability. We focus on key areas for enhancing machine learning operations: a) Model Evaluation: Expanding LLM-based audit platform to support multilingual and multimodal auditing. Developing an LLM-powered testing framework for conversational systems to automate the validation of conversational flows, ensuring scalable, accurate, and efficient end-to-end testing. b) Guardrails: Building common guardrail APIs that teams can integrate to detect and prevent egregious errors, knowledge grounding issues, PII breaches, and biases. c) Deployment Framework support LLM deployments and seamlessly integrate it with our release management processes.- * Bachelor’s degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics) - * 3+ years of relevant work experience in solving real world business problems using AI/ML or applying GenAI and LLMs through prompt engineering techniques. - * Strong hands-on programming skills in Python, SQL. - * Strong analytical thinking - * Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills - * Ability to collaborate effectively across multiple tech and business teams.- * Master's degree with specialization in ML, NLP or Computer Vision preferred - * Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in AI/ML and GenAI Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.