Senior Engineer / Engineer Machine Learning (Banking & Finance Domain)
Senior Engineer / Engineer Machine Learning (Banking & Finance Domain)
Posted on :
28-07-2025
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1 Vacancy
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Job Description
- Collaborate with business stakeholders and cross-functional teams to identify banking-specific challenges (e.g. credit risk fraud detection AML loan defaults) and develop AI-powered solutions.
- Apply advanced machine learning and statistical techniques on structured and unstructured financial data to generate actionable insights.
- Design build and deploy scalable ML models for predictive and prescriptive analytics within core banking digital banking and payment platforms.
- Develop and manage end-to-end ML pipelines including data preprocessing feature engineering model training deployment and monitoring.
- Ensure solutions comply with financial regulations and data governance standards (e.g. CBSL guidelines GDPR PSD2).
- Continuously monitor model performance conduct A/B testing and retrain models to maintain accuracy and reliability.
- Work with DevOps/MLOps teams to deploy and optimize ML solutions in production environments.
Requirements
- Bachelor s degree in computer science IT Data Science or related discipline.
- A master s degree or professional certification in AI/ML or Data Analytics will be an added advantage.
- Minimum 4 years of experience in designing and implementing ML solutions with a portfolio of projects in banking fintech or financial services preferred.
- At least 2 years in production-level model deployment and API integration.
- Strong proficiency in Python ML frameworks (TensorFlow PyTorch Scikit-learn) and data handling using Pandas NumPy.
- Solid understanding of statistical modeling deep learning and NLP techniques.
- Experience with SQL NoSQL and working with large-scale financial datasets.
- Familiarity with cloud platforms (AWS Azure or GCP) and containerization tools (Docker Kubernetes) for ML deployment.
- Hands-on experience in MLOps tools for CI/CD pipeline
- Understanding of banking products digital channels credit scoring risk assessment fraud analytics and regulatory compliance will be a distinct advantage.
- Strong problem-solving skills
- Ability to translate business requirements into AI/ML solutions
- Excellent communication skills and stakeholder management skills
- Commitment to data ethics and regulatory compliance.
Bachelor s degree in computer science, IT, Data Science, or related discipline. A master s degree or professional certification in AI/ML or Data Analytics will be an added advantage. Minimum 4+ years of experience in designing and implementing ML solutions, with a portfolio of projects in banking, fintech, or financial services preferred. At least 2+ years in production-level model deployment and API integration. Strong proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and data handling using Pandas, NumPy. Solid understanding of statistical modeling, deep learning, and NLP techniques. Experience with SQL, NoSQL, and working with large-scale financial datasets. Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes) for ML deployment. Hands-on experience in MLOps tools for CI/CD pipeline Understanding of banking products, digital channels, credit scoring, risk assessment, fraud analytics, and regulatory compliance will be a distinct advantage. Strong problem-solving skills Ability to translate business requirements into AI/ML solutions Excellent communication skills and stakeholder management skills Commitment to data ethics and regulatory compliance.
Employment Type
Full Time
Key Skills
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