Data Science

If you’re looking for a career where you can make a real impression, join Global Service Center (GSC) HSBC and discover how valued you’ll be. HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.We are currently seeking an experienced professional to join our team in the role**Role Purpose**This position provides support and analytical expertise to deliver commercially relevant Global Collections, Underwriting, Credit Bureau and Fraud standards that build functional operational capabilities to deliver results.This position goes beyond the traditional data analysis / BI, you will write complex scripts, automate processes/reporting, answer specific business questions with data. The individual will work closely with operations teams and Sr. Management to translate business requirements into actionable data insights, leveraging Python, as main programming language, and SAS to extract, manipulate and analyze large datasets from the data warehouse and other data sources.We use programming and analytics every day to tackle real business problems, in a nutshell, you will:Pull data from Warehouses stored in SAS Servers / GCP / Hive using Python, SAS, SQL.Analyze data, sometimes structured data from Warehouse and others raw data from other parties.Interpret results to obtain valuable and actionable insights for business.Provide a summary (storytelling) in a clear and compelling manner.Principal Accountabilities:The role holder is responsible for supporting Regional Operations Analytics in support of ensuring strong and sophisticated operations capabilities, aligned to Group standards of expectation. Main activities are:**Business-as-Usual (BAU) Reporting and Monitoring**- Maintain and run existing automated reports, dashboards, and processes.- Ensure data pipelines and recurring outputs (weekly/ monthly/quarterly) are delivered on time and with high accuracy.- Perform quality checks and troubleshoot data issues in regular monitoring.**Data Requests**- Respond to stakeholder data needs with quick and accuracy turnarounds (SQL queries, Python scripts or SAS pulls)- Provide clear, validated datasets for business users and leadership.- Translate ambiguous business questions into structured queries and outputs.**Deep Dive / Exploratory Analysis**- Responsible for complete project lifecycle to investigate business problems or trends using advanced analytics.- Identify root causes, quantify impacts, and uncover actionable insights.- Use Python, SQL and statistical methods to go beyond surface-level reporting.- Communicate findings clearly through visuals (excel, Qlik, looker, plotly, matplotlib) and storytelling to leadership.The role holder is responsible for supporting Regional Operations Analytics in support of ensuring strong and sophisticated operations capabilities, aligned to Group standards of expectation. Main activities are:**Business-as-Usual (BAU) Reporting and Monitoring**- Maintain and run existing automated reports, dashboards, and processes.- Ensure data pipelines and recurring outputs (weekly/ monthly/quarterly) are delivered on time and with high accuracy.- Perform quality checks and troubleshoot data issues in regular monitoring.**Data Requests**- Respond to stakeholder data needs with quick and accuracy turnarounds (SQL queries, Python scripts or SAS pulls)- Provide clear, validated datasets for business users and leadership.- Translate ambiguous business questions into structured queries and outputs.**Deep Dive / Exploratory Analysis**- Responsible for complete project lifecycle to investigate business problems or trends using advanced analytics.- Identify root causes, quantify impacts, and uncover actionable insights.- Use Python, SQL and statistical methods to go beyond surface-level reporting.- Communicate findings clearly through visuals (excel, Qlik, looker, plotly, matplotlib) and storytelling to leadership.Bachelors Degree in Accounting, Finance, Economics, Management with expertise in Data Science / Data Analytics / Business Research in fields: Banking, Credit, Risk, Financial InstitutionsAdvance english (written and oral) - no certifications (C1, B2), english level will be assessed during interviews as the whole process is in english.Proven experience in Python (intermediate level ) for Data Manipulation, Data Automation, Data CleaningProven experience in SQL (intermediate level ) to write complex queries, filtering, grouping, joinsProven experience in Excel (advance level) to clean data, manipulate data (pivots) and sometimes write macros in VBA- Previous experience in Banking / Financial Institutions is a plus.- Exposure to Data Warehouses is a plus.- Exposure to GCP / Hive is