Internship – Data Science

ION Group, Intern, Pisa
We want to innovate the financial services offered by commercial/retail banks in Italy in the areas of wealth management, credit lending, risk management and compliance. Building on our consolidated expertise and product offering in the Capital Markets domain, we want to scale our solutions and frameworks to the commercial/retail banking industry. To do so, we start from the quantitative modelling and analysis of the current processes put in place by our customers, so that we can profile opportunities of automation and prioritize client needs on manual/painful workflows. The resource will be involved in business process analyses of Italian commercial/retail financial institutions and is expected to integrate structured information extracted from interviews with the analysis of literature and documentation to build a quantitative picture of the AS-IS. The analysis will then be complemented with a consequent implementation analysis and product roadmap definition to design the TO-BE and drive product evolutions and developments. The project entails modelling complex business contexts, extracting structured information from unstructured sources, performing quantitative analyses, presenting findings and recommendations to external clients and internal stakeholders, contributing to the definition of product backlogs. ​
What you will learn during your intern:
-          Quantitative modelling of business processes
-          Codification of customer requirements, needs, activities
-          Business intelligence with PowerBI/Excel - Packaging high-quality deliverables for external clients –
-          Data manipulation with Pandas or Spark/Hive  ​
What you need to know:
-          Hands-on experience with BI tools (Excel, PowerBI)
-          Experience with Python data science libraries (pandas, pyspark, sklearn) is nice to have ​
-          Fluent English
We are looking for someone who:
-          is passionate about modelling unknown business contexts with a quantitative approach
-          can find a good trade-off between quality and speed of delivery
-          proactively contribute your insights and ideas in a way that fits existing frameworks of the firm
-          is fond of sharing knowledge with colleagues and documenting your work ​

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