Full stack data scientist/Consultant Specialist

Some careers shine brighter than others.

If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

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 of  Consultant Specialist.

In this role, you will (Key responsibilities)

• Develop end-to-end data science solutions: Design, develop, and deploy data-driven applications, from data collection and preprocessing to model building, deployment, and visualization.
• Data collection and preprocessing: Extract, clean, and transform data from various sources, ensuring data integrity and quality for analysis and modeling tasks.
• Model development and deployment: Create predictive models, machine learning algorithms, and statistical models to solve complex problems. Implement model deployment strategies (e.g., web APIs or microservices) to enable real-time predictions or integration with existing systems.
• Frontend development: Build intuitive and interactive data visualizations or dashboards using web technologies (HTML/CSS/JavaScript) to effectively communicate data insights to stakeholders.
• Backend development: Develop scalable and efficient data pipelines, APIs, or microservices for data ingestion, processing, and storage using programming languages like Python, Java, or Ruby. Implement cloud-based solutions if necessary.
• Collaborate with cross-functional teams: Work closely with data engineers, software developers, and business stakeholders to understand requirements, gather insights, and translate business problems into data science solutions.
• Data exploration and analysis: Conduct exploratory data analysis to identify patterns, trends, and insights from complex datasets. Apply statistical techniques and data visualization to communicate findings effectively.
• Continuous improvement and research: Stay updated with the latest advancements in data science, machine learning, and software development. Research and experiment with new tools, frameworks, and approaches to enhance data science capabilities.