HSBC is hiring for the role of Data Science Analyst!

Responsibilities of the Candidate:

• Support the design, development, and deployment of data science solutions to help achieve IWPB business objectives under the guidance of senior team members.
• Assist in building, validating, and maintaining machine learning models, learning best practices for model lifecycle management.
• Work closely with business stakeholders to understand requirements and help translate them into analytical solutions, with mentorship from experienced colleagues.
• Participate in project tasks such as data extraction, cleaning, and basic analysis, gradually building skills towards independent project management.
• Collaborate with cross-functional teams (business, technology, operations) to ensure alignment and timely delivery of project milestones.
• Prepare and present findings and recommendations to both technical and non-technical audiences using Excel and PowerPoint, with support and feedback from the team.
• Apply foundational analytics and statistical techniques to solve business problems, with opportunities to learn advanced methods.
• Utilize SQL, Python, and/or SAS for data manipulation and analysis, with training and support provided as needed.
• Gain exposure to cloud platforms (e.g., Google Cloud Platform) for scalable data processing and model deployment.
• Stay updated with the latest trends in data science, machine learning, and generative AI, and proactively seek opportunities to learn and apply new techniques.
• Contribute to a culture of continuous learning and upskilling within the team.
• Ensure all work adheres to HSBC’s data governance, privacy, and compliance standards.

Requirements:

• Bachelor’s or master’s degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Engineering, Economics, or related discipline).
• Academic exposure to data analysis, statistics, or machine learning (coursework, projects, internships, or certifications).
• Basic knowledge of programming languages such as Python, SQL, or SAS. Willingness to learn and improve technical skills.
• Familiarity with Excel and PowerPoint for data analysis and presentations.
• Strong analytical and problem-solving skills, with the ability to interpret data and draw meaningful insights.
• Effective communication skills; able to explain technical concepts in simple terms.
• Ability to work collaboratively in a team environment and contribute to group objectives.
• Demonstrated enthusiasm for continuous learning and professional development.
• Interest in the banking and financial services domain is a plus.
• Exposure to data visualization tools (e.g., Tableau, Power BI) or cloud platforms (e.g., GCP) is an advantage, but not required.
• A keen interest in generative AI and related technologies is desirable.