Data Scientist , JCI Measurement and Optimization Science Team

We are seeking a talented customer-focused Data Scientist to join our JCI Measurement and Optimization Science Team (JCI MOST) with a charter to identify the right data build prediction models and optimization capabilities to help inbound service teams make data driven decisions.

This role requires an individual with exceptional data manipulation skill machine learning LLM and excellent cross-functional collaboration skills business acumen and an entrepreneurial spirit to solve business challenges using data and science.

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
- Partner with business stakeholders to deeply understand inbound service programs in Japan and frame ambiguous business problems as science problems and solutions.
- Perform data analysis and build data pipelines to drive business decisions.
- Invent novel science solutions and develop prototypes.
- Review and guide science solutions across the team.
- Publish and socialize your and the teams research across Amazon and external avenues as appropriate
- Leverage industry best practices to establish repeatable science practices principles & processes.



- 2 years of data scientist experience
- 3 years of data querying languages (e.g. SQL) scripting languages (e.g. Python) or statistical/mathematical software (e.g. R SAS Matlab etc.) experience
- Masters degree in Science Technology Engineering or Mathematics (STEM) or experience working in Science Technology Engineering or Mathematics (STEM)

- Ph.D. in Science Technology Engineering or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python Perl or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication

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