Senior Data Scientist

Innowave Tech Pte Ltd; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Innowave Tech, headquartered in Singapore, builds AI platforms to help manufacturers inspect quality, understand complex processes and automate equipment operations.

The role focuses on developing deployed AI solutions for manufacturing challenges in collaboration with engineers and domain experts, with leadership of independent R&D projects to turn solutions into products.

Qualifications

• Diploma, Bachelor's, or Master's degree in Data Science, Statistics, Computer Science, Operations Research, Applied Mathematics, Engineering, or a related field.
• At least 5 years of industry experience in data science or applied machine learning, or 3+ years with a PhD.
• Track record of taking projects from problem formulation to deployment.
• Ability to structure ambiguous requirements with domain experts.
• Strong Python skills and hands-on experience with data and ML libraries.
• Knowledge of supervised, unsupervised, classical, and modern AI techniques.
• Experience in startups or fast-paced, cross-functional teams.

Responsibilities

• Own the data science lifecycle for manufacturing AI solutions from problem formulation to deployment.
• Lead independent R&D projects to turn solutions into products.
• Define data science problems with domain experts from business challenges.
• Select approaches based on context, data availability, and performance constraints.
• Source, clean, and validate data; build, test, and deploy models.
• Contribute to scalable data-processing and model-inference pipelines.
• Communicate findings and recommendations to technical and non-technical stakeholders.

Skills

Python

ML knowledge

Data science

Problem solving

Communication

Education

Bachelor's degree in Data Science/related field

Master's degree preferred

Tools

ML libraries

Job description

Own the data science lifecycle for manufacturing AI solutions, from problem formulation and data preparation through model deployment. Work with engineers and domain experts on equipment health prediction, yield forecasting, and process optimization.

Experience (years) 5+

About Innowave Tech

Innowave Tech turns human expertise into intelligent systems that solve real industrial challenges. Headquartered in Singapore, we build AI platforms that help manufacturers inspect quality, understand complex processes and automate equipment operations.

Our work connects artificial intelligence, software and practical engineering with the realities of the factory floor. From detecting subtle defects to helping equipment respond to changing conditions, we turn specialist knowledge into capabilities that people can use, trust and scale.

We’re looking for people who ask thoughtful questions, care about how things work and take pride in making them better. Join us to tackle demanding problems, bring ideas into real operating environments and help shape how industry works next.

About the role

Develop deployed AI solutions for manufacturing challenges in collaboration with engineers and domain experts. Lead independent R&D projects to turn solutions into products.

Key responsibilities

Work with domain experts to define data science problems from business challenges.

Select approaches based on problem context, data availability, and performance constraints.

Source, clean, and validate data.

Build, test, and deploy machine learning models, accounting for assumptions, limitations, and trade-offs.

Contribute to scalable data-processing and model-inference pipelines.

Communicate findings and recommendations to technical and non-technical stakeholders.

Lead independent R&D projects to turn solutions into products.

Required skills and experience

Diploma, Bachelor's, or Master's degree in Data Science, Statistics, Computer Science, Operations Research, Applied Mathematics, Engineering, or a related field.

At least 5 years of industry experience in data science or applied machine learning, or 3+ years with a PhD.

Track record of taking projects from problem formulation to deployment.

Ability to structure ambiguous requirements with domain experts.

Strong Python skills and hands-on experience with data and machine learning (ML) libraries.

Knowledge of supervised, unsupervised, classical, and modern AI techniques.

Experience in startups or fast-paced, cross-functional teams.

Good to have

Sensor data, time series analysis, or signal processing.

Optimization algorithms, such as genetic algorithms or Bayesian optimization.

Statistical analysis and modeling.

Retrieval-augmented generation (RAG), agentic AI, harness engineering, or knowledge bases for AI agents.

Semiconductor or high-tech manufacturing background.