We are currently looking for an experienced Data Scientist / ML Engineer to join the team and take a leading role in validating, evaluating, and overseeing machine learning models and AI solutions.
Key Responsibilities
- Review and validate machine learning models proposed by external vendors
- Evaluate model performance using metrics such as accuracy, precision, recall, and AUC
- Assess model robustness, bias, and fairness, particularly for risk profiling models
- Analyze and validate NLP model outputs and performance
- Validate feature engineering approaches across structured and unstructured datasets
- Monitor model performance over time, including model drift and data drift
- Define and implement model validation frameworks and documentation standards
- Support explainability and transparency requirements for regulatory compliance
- Act as a technical authority for AI/ML during implementation phases
- Provide recommendations for model improvements and optimizations
Qualifications & Experience
Minimum Qualifications:
- Bachelor’s degree in Computer Science, Information Technology, or a related field
Experience:
- 5-8 years of experience in Data Science, Machine Learning, or a related field
Technical Skills
- Strong understanding of machine learning algorithms, including classification and risk scoring models
- Solid knowledge of model validation techniques and statistical evaluation methods
- Hands-on experience with Python
- Experience with model monitoring and performance tracking tools
- Familiarity with NLP techniques such as tokenization, embeddings, and transformers
- Understanding of AI governance, model explainability (e.g., SHAP, LIME), and ethical AI practices
- Experience validating third-party or vendor-provided models
Preferred Qualifications
- Familiarity with Azure ML and MLOps practices
- Knowledge of AI regulatory frameworks and compliance standards
- Experience managing the full machine learning lifecycle
