Data Science Expert | CBQ

Commercial Bank Intelligence Unit (CBIU) is a diverse cross functional team providing data, analytics, and business intelligence to the bank. The team works on a diverse universe of data use cases with the objective to enable the Bank to take data driven business decisions, enhance efficiency and optimize returns.

At Commercial Bank, data is a key driver in strategic decision making; the incumbent is required to have a thorough understanding of data analytics, data management principles and have ability to help the bank derive maximum value from the data available. Previous experience with data science and advanced analytical techniques, as well as AI and Machine Learning in a banking context would be a major success factor.

The skills needed for the Data Science Expert include technical knowledge and problem-solving; focus on delivery, stakeholder’s management and strategic thinking. The prospective candidate is expected to help take the bank’s data science capabilities to the next level; building on a good foundation but accelerating both the capability development and the exploitation of benefits.

Key Responsabilities:

The Data Science Expert works with business executives and various departments within the Bank to provide advanced data science solutions for implementation. Use cases can include but would not be limited to intelligent character recognition, computer vision, behavioral analyses, early warning signs analyses, generative artificial intelligence, NLP, LLM, hyper-personalization etc.
The Data Science Expert designs, tests and launches innovative and complex analytic models, utilizing a blend of contemporary and traditional data mining techniques, which he applies to both structured and unstructured data sets.
The Data Science Expert works on the development of big data capabilities and utilization as well as the coordination of cross-functional analytic initiatives.

Key Responsibilities:

• Work on data mining and collection procedures
• Ensure data quality and integrity
• Interpret and analyze data problems
• Conceive, plan and prioritize data projects
• Build analytic systems, predictive models and artificial intelligence capabilities
• Test performance of data-driven products
• Visualize data and create innovative reports and present to key stakeholders including most senior Management of the Bank
• Experiment with new models and techniques