- 経験
- 5+ yrs
- 給料
- —
- 求人情報
- 1
- 投稿済み
- 16時間前
Where you'll work
仕事内容
Role overview
The Senior Associate role in Data Science and Machine Learning is centered on turning raw data into practical insights and technical solutions for Ford Motors. The position blends analytics, machine learning, and software delivery to support smarter business decisions and improve operational systems.
What you will do
- Study unstructured and raw datasets to uncover trends, patterns, and actionable recommendations.
- Apply advanced analytical methods such as machine learning, predictive modeling, statistics, mathematics, and other data science techniques.
- Work closely with business partners to clarify needs and shape the right analytical approach.
- Build and implement data analysis workflows, algorithms, models, and experiments.
- Use data mining, predictive and prescriptive analytics, and statistical methods to surface meaningful findings.
- Create scalable and efficient processes for data loading, enrichment, and analysis, with automation as a key goal.
- Stay current with evolving tools, methods, and developments in data science, machine learning, and analytics.
- Deliver middleware APIs ready for production that can ingest, combine, and expose operational data.
- Implement and support an agentic AI orchestration layer for anomaly detection and structured recommendations.
- Connect AI-based reasoning and recommendations to user-facing applications through APIs and webhooks.
- Build modular, well-tested code in partnership with internal teams using Git-based repositories.
- Create training documents and knowledge-transfer materials for engineering and product stakeholders.
Skills and experience
This role calls for hands-on expertise in J2EE, Python, logistics, and machine learning, along with practical exposure to API development, advanced data migration, and data management. Prior work in automotive or supply chain/logistics environments is an advantage.
Education and eligibility
A bachelor’s degree is required. A certification in a relevant discipline is preferred. The role is intended for candidates with at least 5 years of specialized professional experience.
Additional notes
The position appears to focus on production-grade analytics and engineering delivery, including automation, integration, collaboration, and documentation for internal teams.