We are seeking a highly skilled Data Scientist with expertise in data analytics, insight generation, and optimization for manufacturing data.
The ideal candidate will leverage AI/ML, optimization algorithms, and various advanced analytics techniques to drive operational efficiency and process improvements.
About Innowave Tech Singapore
Innowave Tech is an Artificial Intelligence (AI) company offering solutions for the Semiconductor and Advanced Manufacturing industry.
We are an agile, innovation-driven company operating at the intersection of advanced manufacturing and AI.
We collaborate closely with domain experts to solve real-world challenges using cutting-edge data science.
If you are passionate about turning complex technical problems into tangible impact, we want to hear from you.
Why Join Us
Work on meaningful problems that make a difference in high-impact industries
Join a small team that values initiative, ownership, and clear communication
Your Role and Impact
As a Data Scientist, you will be at the forefront of transforming complex domain challenges into impactful AI-driven solutions.
You will work side-by-side with engineers, domain experts, and stakeholders to uncover opportunities, shape problem statements, and apply the right data science approaches to solve real-world problems.
You will own the full data science lifecycle, from understanding raw data to deploying robust models, while balancing scientific rigor with practical implementation.
Your ability to independently explore data, assess quality, and deliver insights will directly influence decision-making and product development.
Your work will not be isolated to experimentation.
You will contribute to solutions and product developments that bridge the gap between theory and implementation.
Whether it is predicting equipment health, predicting manufacturing yield, or optimizing processes, your contributions will drive measurable impact in a fast-moving, innovation-driven environment.
Work closely with domain experts to understand business challenges, formulate problem statements, and translate them into data science solutions.
Evaluate and select appropriate approaches based on problem context, data availability, and performance constraints.
Independently source, clean, and validate data for analysis and modeling, ensuring data quality, consistency, and reliability.
Build, test, and deploy machine learning models with an awareness of model assumptions, limitations, and trade-offs.
Communicate findings and recommendations clearly to both technical and non-technical stakeholders.
Contribute to the design and implementation of robust, scalable pipelines for data processing and model inference.
Educational Background:
Minimum Poly, Bachelor’s, or Master’s degree in Data Science, Statistics, Computer Science, Operations Research, Applied Mathematics, Engineering, or a related field.
Technical skills:
Must-haves:
Nice-to-haves:
Be careful - Don’t provide your