Global AI & Data Product Lead

Worldwide Flight Services Holland B.V.; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

SATS is investing in a small number of high-impact AI and data products intended to operate across its global station network. We are looking for a Lead, AI & Data Products to take that ownership.

This is a senior individual contributor role for an engineer or applied scientist who has moved into product leadership, not a product manager with adjacent technical exposure. You will reason about model design, data architecture and production trade-offs at the level of the engineers building the

Qualifications

• 10+ years in engineering, AI or data science with production experience.
• Proven ownership of technical products end to end and scaling multi-site.
• Expertise in forecasting, optimization, simulation or GenAI.
• Proficient in Python and SQL and modern ML stack.
• Ability to influence senior stakeholders without direct reporting lines.
• Aviation/logistics experience is a plus.

Responsibilities

• Own the technical product end to end for AI and data initiatives.
• Be single-threaded owner for adoption and business case across stations.
• Translate operational problems into technical solutions.
• Lead across engineering, data science, operations and regional teams.
• Review designs and contribute to code; hands-on with architecture decisions.
• Ensure production quality: robustness, monitoring, latency and cost.

Skills

10+ years exp

Product ownership

Forecasting

Optimization

Simulation

GenAI

Python & SQL

ML stack

Stakeholder influence

Aviation/logistics

Education

Bachelor's/MSc/PhD in CS/Engineering/Data Science

Job description

SATS is investing in a small number of high-impact AI and data products intended to operate across its global station network. We are looking for a Lead, AI & Data Products to take that ownership.

This is a senior individual contributor role for an engineer or applied scientist who has moved into product leadership, not a product manager with adjacent technical exposure. You will reason about model design, data architecture and production trade-offs at the level of the engineers building the