End-to-End Manufacturing AI Data Scientist

Innowave Tech Pte. Ltd.; Singapore; On-site; SGD 90,000 - 180,000; Full time

Job summary

Innowave Tech Singapore seeks a Data Scientist to drive AI-based insights for manufacturing data and to optimize processes. You will own the full data science lifecycle, from data understanding to model deployment, collaborating with engineers, domain experts, and stakeholders to ensure practical, measurable impact.

You will apply ML to predict equipment health, yield, and process performance, leveraging Python, analytics, and optimization techniques in a fast-moving, innovation-driven

Qualifications

• Minimum 5 years of data science experience in industry (or 3+ years with PhD)
• Proven ability to take projects from problem formulation to deployment
• Experience working with domain experts to translate requirements into models
• Hands-on data wrangling, cleaning, and validation
• Strong programming skills in Python and ML libraries
• Familiarity with startup or fast-paced cross-functional teams

Responsibilities

• Understand business challenges and translate them into data science solutions
• Evaluate approaches based on data availability and constraints
• Source, clean, and validate data for analysis and modeling
• Build, test, and deploy ML models with consideration of assumptions and trade-offs
• Communicate findings to technical and non-technical stakeholders
• Contribute to robust, scalable data pipelines for processing and inference
• Lead independent R&D projects to productize solutions

Skills

Data analysis

Python programming

Model development

Data wrangling

Communication

Problem solving

Independent learner

Cross-functional collaboration

Education

Bachelor’s degree in data science, statistics, CS, OR, or related field

Master’s preferred

Tools

Pandas

Scikit-learn

TensorFlow/PyTorch

SQL

Job description

Innowave Tech Singapore seeks a Data Scientist to drive AI-based insights for manufacturing data and to optimize processes. You will own the full data science lifecycle, from data understanding to model deployment, collaborating with engineers, domain experts, and stakeholders to ensure practical, measurable impact.

You will apply ML to predict equipment health, yield, and process performance, leveraging Python, analytics, and optimization techniques in a fast-moving, innovation-driven