Data & AI Engineer

Innoxsea; Singapore; On-site; SGD 17,000 - 26,000; Full time

Job summary

Innoxsea in Singapore is seeking a Data & AI Intern to join the founding team and help build the knowledge base and platform intelligence. You will work with the team to transform raw information into structured knowledge, perform data acquisition and cleaning, and model relationships within the innovation ecosystem.

The role is ideal for someone pursuing or recently completing a Master or PhD in a related quantitative field, with a passion for data, AI, and scalable data pipelines.

Qualifications

• Pursuing or completed Master/PhD in a quantitative field.
• Strong data engineering and analytical skills.
• Experience with Python and data libraries is a plus.

Responsibilities

• Knowledge Base Development: construct and validate the proprietary knowledge base from diverse data sources.
• Systematic Data Acquisition: collect, process, and integrate large volumes of structured and unstructured data.
• Data Integrity and Enrichment: clean, normalize, and enrich data to ensure accuracy.
• Relational Modeling: analyze and model relationships between entities to power the platform.

Skills

Knowledge base dev

Data acquisition

Data cleaning

Relational modeling

Python

Pandas/NumPy

SQL/NoSQL

Analytical thinking

Education

Master's or PhD in CS/Data Science/IS/Statistics/Computational Biology

Tools

SQL

NoSQL

Web scraping

Job description

Innoxsea is building a vertical AI intelligence platform for cross-border innovation and strategic alliances in APAC, starting with Life Sciences and deep tech. Our mission is to connect ideas, talent, and capital across borders by creating a dynamic, multi-relational map of the entire innovation ecosystem.

At the heart of our platform is a proprietary data foundation—a sophisticated “brain” that understands the relationships within the ecosystem. We are looking for a curious and driven Data & AI Intern to join our founding team and play a direct role in building this foundational asset.

What You’ll Do:

As a Data & AI Engineer (or Intern), you will be on the front lines of building our company’s core data moat. You will work directly with the founding team to transform raw information into structured intelligence. Your responsibilities will include:

• Knowledge Base Development: Play a key role in the end‑to‑end construction of our proprietary knowledge base, from identifying novel data sources to structuring and validating information at scale.
• Systematic Data Acquisition: Employ modern techniques to systematically acquire, process, and integrate large volumes of structured and unstructured data from diverse public sources.
• Data Integrity and Enrichment: Implement processes for data cleaning, normalization, and enrichment to ensure the highest standards of accuracy and completeness.
• Relational Modeling: Analyze and model the complex relationships between different entities within the innovation ecosystem to power our platform's intelligence layer.

Who You Are:

• Detail‑Oriented & Analytical: You have a keen eye for detail and a methodical approach to problem‑solving. You understand that in data, quality and accuracy are paramount.
• A Proactive Learner: You are intellectually curious, a self‑starter, and are not afraid to ask questions. You are passionate about the potential of data and AI to solve meaningful problems.
• A Data Enthusiast: You are excited by the prospect of working with large, complex datasets and transforming them into structured knowledge.
• Currently pursuing or recently completed Mater or PhD degree in Computer Science, Data Science, Information Systems, Statistics, Computational Biology, or a related quantitative field.

Bonus Points:

• Hands‑on experience with agentic AI frameworks or building AI agents.
• Familiarity with databases (SQL or NoSQL).
• Experience with automated web data extraction techniques.
• Proficiency in Python and data manipulation libraries (e.g., Pandas, NumPy).

Why Join?

• Your work is core to the product, not a side project.
• Hands‑on exposure to ecosystem intelligence and real startup building.
• Direct collaboration with the founding team; high ownership and fast learning.