Position Description:
Employees in this job function are responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc. Key Responsibilities: 1) Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making 2) Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making 3) Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends 4) Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation 5) Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Fully Functional Middleware API: A production-ready middleware layer that ingests, aggregates, and exposes the 6 core operational data points. Agentic AI Orchestrator: A deployed multi-agent system that autonomously monitors the middleware data, flags anomalies, and generates structured recommendation JSON payloads. Human-in-the-Loop (HITL) Dashboard Integration: APIs and webhooks that feed the AI's reasoning, recommendations, and confidence scores into our front-end application. Co-Developed Codebase: A clean, modular, and fully tested Git repository co-authored with our internal team. Coaching Playbook: A comprehensive training package and transfer-of-ownership document for our internal engineering and product teams
Skills Required:
J2EE, Logistics, Python, Machine Learning
Skills Preferred:
AIPGEE, Advance data Migration, API, Data Management
Experience Required:
Specialist Exp: 5+ experience in relevant field
Experience Preferred:
Automotive Supply Chain - Logistics
Education Required:
Bachelor's Degree
Education Preferred:
Certification Program
Additional Information:
4 days on site.

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