About Snappymob Malaysia

Snappymob is a boutique technical consultancy specializing in fintech and financial services in Malaysia and APAC. We craft cutting-edge web and mobile solutions that push boundaries, tackling the impossible challenges that others won't even attempt.

Our vibrant team of 100+ innovators from 18 nationalities brings together world-class engineers, QA specialists, and designers. We're obsessed with our craft, thrive on continuous learning, and collaborate to turn ambitious ideas into reality.

About the role:
We are looking for a strong individual contributor to help us design, build, and deploy practical machine learning solutions in real-world financial environments.

This is not a “build an entire department from scratch” role. You will work closely with experienced engineers and stakeholders to turn well-defined problem statements into reliable, production-ready ML systems.

Key Responsibilities

• Design and develop machine learning models for use cases such as predictive modeling, risk scoring, anomaly detection, and time-series forecasting.

• Translate business problem statements into clear ML approaches and measurable success criteria.

• Perform data exploration, feature engineering, model training, validation, and performance tuning.

• Build and maintain reliable data pipelines for structured and unstructured datasets.

• Deploy models into production environments and support monitoring, evaluation, and continuous improvement.

• Contribute to experimentation with modern AI approaches (including LLMs or RAG systems) where relevant.

• Document assumptions, methodologies, and results to ensure clarity and maintainability.

What would you need? 

• Master’s or PhD in a quantitative field such as Data Science, Machine Learning, Computer Science, Statistics, or Applied Mathematics, or equivalent experience.

• Experience applying data science or machine learning models in a financial services, fintech, or capital markets setting.

Advantage:

• Familiarity with financial market concepts such as asset classes, risk metrics, portfolio construction, trading strategies, or market microstructure.

You’re Likely a Great Fit If:

• You have built and deployed ML models that delivered measurable business outcomes.

• You are comfortable working hands-on with Python and common ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy).

• You understand the practical trade-offs between model complexity, performance, and maintainability.

• You have experience with model evaluation techniques such as cross-validation or backtesting.

• You are familiar with version control, containerization (Docker), and basic cloud or MLOps workflows.

• You can work independently with clear goals, without requiring constant direction.

Why join us?

• Meaningful Projects: Work on real-world financial and fintech problems with tangible impact.

• Employer-Sponsored Work Visa: Full visa sponsorship for relocation (if applicable).

• Career Growth: Mentorship, technical exposure, and continuous learning.

• Flexible Work Arrangement: 2 days work-from-home, 3 days in-office, with flexible working hours.

• Accessible Location: Office conveniently located near the LRT.

• Competitive Compensation: Salary commensurate with experience and capability.