Fraud ML Lead — GCP & Cost-Optimized Data Science

Capco; Hong Kong; Hybrid; HKD 900,000 - 1,300,000; Full time

Job summary

Capco in Hong Kong is seeking a Data Scientist Lead to help clients optimise fraud models, ML platforms and Google Cloud infrastructure. You will translate detailed analysis into practical, implementation-ready recommendations and take a hands-on approach to improving model performance and run-cost on GCP.

Collaborating with IT, data scientists and fraud stakeholders, you will design cost-efficient pipelines, support responsible AI practices and provide guidance from code to production while

Qualifications

• Strong hands-on experience in data science, machine learning engineering or ML platform optimisation.
• Deep experience with Google Cloud Platform and the optimisation of cloud compute, storage, networking and ML workloads.
• Strong Python and SQL skills, together with experience building, validating, deploying and optimising production ML models and data pipelines.

Responsibilities

• GCP engineering: Lead hands-on design, diagnostics and optimisation across compute, storage and network services.
• Fraud ML modelling: Support the development, validation and deployment of fraud and ML models end-to-end.
• ML and data pipelines: Optimise pipelines spanning ingest, transformation, feature creation and serving, training and inference.
• Big data and distributed processing: Develop and tune large-scale batch and streaming workloads using Spark or similar technologies.
• Engineering excellence: Apply strong Python and SQL skills alongside CI/CD, automated testing and disciplined code review.

Skills

GCP engineering

Fraud ML modelling

Python

SQL

CI/CD

Tools

Spark

TensorFlow

Job description

Capco in Hong Kong is seeking a Data Scientist Lead to help clients optimise fraud models, ML platforms and Google Cloud infrastructure. You will translate detailed analysis into practical, implementation-ready recommendations and take a hands-on approach to improving model performance and run-cost on GCP.

Collaborating with IT, data scientists and fraud stakeholders, you will design cost-efficient pipelines, support responsible AI practices and provide guidance from code to production while