Senior Data Science Expert

About the role

Responsible for developing advanced machine learning models for banking use cases such as pricing optimization, customer propensity modelling, and recommendation systems. The senior role combines deep statistical and ML expertise with extensive banking domain knowledge.

Key responsibilities

• Design and develop ML models for pricing, propensity, and recommendation systems.
• Apply banking domain knowledge to translate business problems into actionable ML solutions.
• Conduct exploratory data analysis, create visualizations, and communicate insights to stakeholders.
• Build prototypes in Python, document methodology, and collaborate with ML engineers to move models to production.

Required profile

• Master’s degree in a quantitative field (Finance, Economics, Statistics, Mathematics, etc.).
• 8+ years of data science/quantitative analysis experience, with at least 5 years in banking or financial services.
• Proven track record delivering ML models in pricing, propensity or recommendation domains.
• Experience with model validation, governance, and regulatory requirements (e.g., IFRS 9, Basel).

Required skills

• Python (pandas, scikit‑learn, XGBoost, etc.)
• SQL (advanced queries, stored procedures, window functions)
• Machine learning techniques: supervised/unsupervised learning, deep learning frameworks (TensorFlow, PyTorch)
• Data visualization and reporting tools
• Version control with Git
• Basic Spark knowledge and MLOps concepts (MLflow, TFX)

What we offer

• Competitive compensation and benefits.
• Innovation‑driven, digital‑first environment with latest tools.
• Opportunities for global partnerships and international exposure.
• Focus on employee well‑being, work‑life balance, and DEI commitment.