Data Scientist

Job Description

Appealing points:

• Create real impact through data science on the factory floor Analyze machine, sensor, and process data to drive predictive maintenance, reduce downtime, and improve manufacturing performance.
• Lead advanced analytics for predictive maintenance Apply time-series modeling, anomaly detection, and machine learning to build and deploy end-to-end solutions in industrial environments.
• Bridge data insights and operational action Work closely with maintenance and operations teams to translate complex analytics into practical, value-driving decisions.

Annual Salary: 7 million and above

Responsibilities

• Analyze machine, sensor, and process data to uncover failure patterns, downtime drivers, and optimization opportunities.
• Build and deploy predictive maintenance models (failure prediction, RUL, anomaly detection).
• Partner closely with maintenance and operations teams to translate shop-floor challenges into analytical solutions.
• Lead end-to-end data science workflows — from data cleaning and feature engineering to modeling, validation, and productionization.
• Communicate insights clearly and confidently to technical and non-technical stakeholders.
• Support implementation of digital/AI initiatives across manufacturing lines.

Job Qualifications:

• 5+ years in data science with hands-on experience in manufacturing or industrial environments.
• Strong exposure to maintenance-related analytics (equipment health, failure modes, reliability metrics, SPC, etc.).
• Deep experience with time-series modeling, anomaly detection, and machine learning (supervised & unsupervised).
• Proficiency with Python, SQL, and common DS libraries (Pandas, Scikit-Learn, TensorFlow/PyTorch preferred).
• Experience working with industrial data sources (PLC data, historians like OSIsoft PI, MES data, SCADA).
• Comfortable interfacing with shop-floor teams; able to ask the right questions and translate insights into action.
• Strong communication skills — fluent, structured, and persuasive.
• Business-level English; Japanese proficiency a strong advantage.

Nice-to-Have

• Background in mechanical, industrial, or manufacturing engineering.
• Experience deploying models via cloud platforms (AWS/GCP/Azure).
• Familiarity with TPM, Lean, Six Sigma, or reliability engineering concepts

Japanese Languages: Fluent japanese level (JLPT N1) and business level english required

Company Description: 

Company helps future-proof your business through a forward-thinking, fluidic, and CARING mindset. We excel at digital engineering and help our clients become human-centric, digital-first organizations, augmenting their ability to be responsive, efficient, intimate, creative, and sustainable. Today, we are 19,000 experts across 36 countries, forming a Nation of Nagarrians, ready to help our customers succeed.