Data Scientist (Secondment)

Rise Associates Asia Limited; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

Rise Associates Asia Limited seeks an experienced Data Scientist for a secondment engagement with a top-tier enterprise client. You design, build and deploy production-grade ML models and robust MLOps pipelines for monitoring and lifecycle management.

You will collaborate with IT and business teams to translate complex questions into scalable technical solutions using Python, PySpark, SQL, and cloud platforms, while emphasizing clear communication and agile practices.

Qualifications

• Minimum 4+ years of hands-on data science experience with production ML deployments.
• Degree (or equivalent) in a quantitative field as listed.

Responsibilities

• End-to-End ML development, proposing, designing, and optimizing models.
• Production deployment and MLOps, drift detection, monitoring, and lifecycle management.
• Adherence to software engineering practices including testing and code reviews.
• Collaborate with business teams to translate questions into scalable solutions.

Skills

Python

PySpark

SQL

PyTest

Azure Databricks

Azure Cloud Stack

CI/CD

MLOps

Education

Quantitative degree (CS, Econometrics, Math, OR, Stats)

Tools

Azure Databricks

Azure Cloud Stack

PyTest

Job description

Summery: We are seeking an experienced Data Scientist on a secondment engagement with a top-tier enterprise client.

In this role, you will bridge the gap between advanced machine learning and real-world business impact. You will design, build, and deploy production-grade ML models while building robust MLOps pipelines for ongoing model monitoring and lifecycle management.

Responsibilities:

• End-to-End ML Development: Propose, design, and optimize machine learning models (e.g., XGBoost, Deep Neural Networks) grounded in mathematical rigor.
• Production Deployment & MLOps: Partner with IT engineering teams to deploy models to production and create repeatable pipelines for evaluation, performance drift detection, and monitoring.
• Software Engineering Standards: Deliver clean, maintainable, production-grade code adhering to best practices like unit testing (pytest), code reviews, and structured repos.
• Business & Stakeholder Engagement: Collaborate directly with business teams to translate unstructured business questions into scalable technical solutions and actionable insights.

Requirements:

• Experience: Minimum 4+ years of solid hands-on data science experience, with a proven track record of deploying ML models into production environments.
• Education: Degree (or equivalent) in Computer Science, Econometrics, Mathematics, Operations Research, Statistics, or a related quantitative field.
• Technical Stack:
  • Expert-level skills in Python, PySpark, and SQL.
  • Hands-on experience with testing frameworks like pytest.
  • High proficiency in cloud environments—Azure Cloud Stack and Azure Databricks strongly preferred.
• MLOps & Engineering Practices: Strong background in MLOps (model versioning, experiment tracking, CI/CD, drift detection) and Git-based code reviews/pull requests.
• Soft Skills: Excellent presentation and communication skills, with a demonstrated ability to translate complex mathematical and technical concepts for both technical and non-technical stakeholders. Experience in Agile environments (Jira) is a plus.