Sr. Applied Scientist, JCI Measurement and Optimization Science Team
Amazon · Tokyo, Japan · Machine Learning Science
senior
machine learning
Applied Scientist
ic
3+ yrs Master's
· Posted Feb 16, 2026
Skills
AI Summary
Build scalable ML and LLM systems to detect pricing defects, implement intelligent corrections, and measure intervention impacts across millions of products. Requires expertise in machine learning, causal inference, system architecture, and cross-functional collaboration to drive pricing quality improvements.
We are seeking a talented, customer-focused applied scientist to join our JCI Measurement and Optimization Science Team (JCI MOST), with a charter to build scalable systems that automatically detect pricing defects, implement intelligent corrections, measure intervention impacts, and deliver data-driven pricing strategies to leadership.
This role requires an individual with exceptional machine learning, LLM, and Causal Inference expertise, strong system architecture capabilities, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit to drive measurable improvements in pricing quality and competitiveness.
We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and thrives in a fast-paced, data-driven environment.
Key job responsibilities
Key Job Responsibilities
• Build scalable defect detection systems that automatically identify pricing anomalies, competitive gaps, and quality issues across millions of products using ML and LLM models and real-time monitoring
• Deploy automated defect remediation with intelligent pricing recommendations, and validation frameworks that reduce manual intervention requirements
• Measure impact and drive strategy by establishing robust measurement frameworks, designing large-scale experiments, building attribution models, and developing executive dashboards that translate findings into actionable insights for leadership
• Lead cross-functional collaboration by partnering with product, engineering, and science teams to deploy solutions at scale while communicating complex technical concepts clearly to executive audiences
• Stay at the forefront of innovation by applying state-of-the-art techniques in ML, deep learning, LLM, and causal inference to pricing quality challenges while fostering rapid experimentation and continuous learning
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with neural deep learning methods and machine learning
- Knowledge of advanced causal modeling techniques, both in experimental and observational settings
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.
This role requires an individual with exceptional machine learning, LLM, and Causal Inference expertise, strong system architecture capabilities, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit to drive measurable improvements in pricing quality and competitiveness.
We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and thrives in a fast-paced, data-driven environment.
Key job responsibilities
Key Job Responsibilities
• Build scalable defect detection systems that automatically identify pricing anomalies, competitive gaps, and quality issues across millions of products using ML and LLM models and real-time monitoring
• Deploy automated defect remediation with intelligent pricing recommendations, and validation frameworks that reduce manual intervention requirements
• Measure impact and drive strategy by establishing robust measurement frameworks, designing large-scale experiments, building attribution models, and developing executive dashboards that translate findings into actionable insights for leadership
• Lead cross-functional collaboration by partnering with product, engineering, and science teams to deploy solutions at scale while communicating complex technical concepts clearly to executive audiences
• Stay at the forefront of innovation by applying state-of-the-art techniques in ML, deep learning, LLM, and causal inference to pricing quality challenges while fostering rapid experimentation and continuous learning
Basic Qualifications
- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with neural deep learning methods and machine learning
- Knowledge of advanced causal modeling techniques, both in experimental and observational settings
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.