Senior Data Scientist (Finance Model)

Key Accountabilities (1)

• Analyze large and complex banking datasets to identify trends, patterns, and opportunities.
• Develop and implement predictive models and machine learning algorithms to improve customer segmentation, product performance, financial performance, and marketing strategies.
• Collaborate with cross-functional teams including finance, business unit, marketing, Data and IT to understand business needs and deliver data-driven solutions.
• Communicate findings and insights effectively to both technical and non-technical stakeholders.
• Ensure data quality and integrity by performing data cleaning, validation, and preprocessing.
• Stay updated with the latest developments in data science, machine learning, and banking regulations.
• Support the automation of data processes and reporting.

Key Accountabilities (2)

Development languages: Python, R, SQL, Databrick, tools: Jupyter Notebook, VS Code, PyCharm
Analysis and visualization: Power BI, Tableau
Machine Learning library: scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch 

Success Profile - Qualification and Experiences

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• Proven experience as a Data Scientist, preferably in the banking or financial services industry.
• Strong proficiency in programming languages such as Python, R, or SQL.
• Experience with machine learning frameworks and libraries
• Solid understanding of statistical analysis, data mining, and predictive modeling techniques.
• Familiarity with banking products, regulations, and risk management practices is a plus.
• Excellent problem-solving skills and attention to detail.
• Strong communication and presentation skills.