Mitsubishi Logisnext Americas Inc. is looking to build an intelligence layer for real-world operations where safety, performance, and productivity intersect by leveraging AI/ML to interpret and act on complex machines and behavioral data, aiming to solve problems that directly affect the movement of goods, the efficiency of workforces, and the uptime of critical equipment.
Requirements
- Proven experience building and deploying machine learning models in production environments (e.g., predictive, diagnostic, time-series models)
- Strong proficiency in Python and modern ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow)
- Experience working with real-world, high-volume, structured and semi-structured datasets, ideally involving sensor or operational data
- Hands-on expertise in feature engineering, data exploration, and statistical analysis
- Demonstrated ability to lead and develop technical teams, including mentoring and resource planning
- Experience aligning AI/ML solutions to product strategy, stakeholder needs, and real-world use cases
- Demonstrated ability to lead a team while actively contributing as a hands-on practitioner, comfortable setting vision, delegating, & deep technical work
Responsibilities
- Lead and manage the applied analytics team, including Data Engineering and Prompt Engineering. Provide direction, mentorship, performance feedback, and resource planning to ensure team success.
- Design, build, and deploy machine learning models to drive diagnostic, predictive, and prescriptive insights based on operational, behavioral, and event-based data.
- Shape and guide the analytics product roadmap in partnership with Product, Engineering, and Business stakeholders—ensuring ML/AI development aligns with platform strategy and stakeholder needs.
- Work hands-on with data, including exploration, feature engineering, experimentation, and model refinement—ensuring solutions are accurate, scalable, and production-ready.
- Collaborate with internal and third-party partners to align data models, AI/ML use cases, and product integrations with broader ecosystem objectives.
- Contribute to the development of user-facing AI interfaces, such as natural language experiences, intelligent recommendations, and analytics workflows.
- Represent the analytics function internally and externally, including presentations to stakeholders, customers, and executive leadership.
Other
- Bachelor’s degree in a technical or quantitative field, such as Computer Science, Data Science, Engineering, or Statistics
- 7+ years of experience
- This is a hybrid position (3 days per week in office, 2 days working from home).
- Up to 20% travel may be required, including some international travel.
- Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.
