Data Scientist
HSBC Group, Sheffield
Data Scientist
Salary not available. View on company website.
HSBC Group, Sheffield
- Full time
- Permanent
- Onsite working
Posted 1 week ago, 25 Jun | Get your application in now before you're too late!
Closing date: Closing date not specified
job Ref: 3d90a512a3a74fa2b49a74c205b2b3a4
Full Job Description
Technology teams in the UK work closely with our global businesses to help design and build digital services that allow our millions of customers around the world, to bank quickly, simply and securely. They also run and manage our IT infrastructure, data centres and core banking systems that power the world's leading international bank. Our multi-disciplined teams include DevOps Engineers, IT Architects, Front and Back End Developers, Infrastructure specialists, Cyber experts, as well as Project and Programme managers. We are looking for a highly experienced and visionary Data Scientist to drive innovation through data and artificial intelligence. This role is the perfect fit for an individual who can identify, lead, and execute impactful data science and AI projects, transforming complex data into strategic insights within a dynamic environment. About the Role: You will be responsible for leveraging advanced analytical techniques and cutting-edge AI technologies to address critical business challenges. This involves proactively identifying opportunities, leading initiatives from concept to deployment, and fostering a culture of data-driven decision-making. Responsibility
- Strategic Data Insights: Proactively identify and lead key data-driven initiatives, with a focus on improving performance and efficiency, particularly in the DevSecOps space e.g. DORA Metrics
- Rapid Experimentation: Design and execute "learn-fast" experiments to explore new ideas, validate hypotheses, and accelerate learning and innovation
- Advanced Analytics & Visualisation: Conduct in-depth data analysis, develop sophisticated predictive models, and create compelling visualisations to communicate actionable insights to diverse stakeholders through strong story telling
- Data Science Thought Leadership: Stay at the forefront of Data Science and AI technology, including generative AI, discerning impactful advancements from emerging trends, and advising on their strategic application to enhance capabilities
- Documentation & Collaboration: Develop and maintain comprehensive documentation for data models, system assumptions, and both business and technical workflows, ensuring transparency and knowledge sharing
- Mentorship & Influence: Mentor other data scientists and foster an environment of continuous learning and excellence
- Lead AI Initiatives: Drive the end-to-end lifecycle of AI and machine learning projects, including problem definition, data acquisition, model development, experimentation, and operationalisation Experience/Skill Sets
- Experience: Demonstrable experience in data science, showing strong expertise in data processing, advanced analytics, and model development
- Expertise in SQL and statistical programming languages (e.g., Python, R), coupled with a deep understanding of data modelling principles
- Mastery of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and their application in complex problem domains
- Extensive experience with MLOps principles and tools for model deployment, monitoring, versioning, and lifecycle management
- Proven experience with analytics and visualisation toolkits such as Qlik, Looker, or similar platforms along with Basic API skills (e.g., Postman) for integration and data ingestion
- Proficiency with the latest AI technology stack and practical experience with generative AI applications, including prompt engineering and fine-tuning
- Strong experience with cloud platforms (e.g., GCP, AWS, Azure) and their data/ML services (e.g., BigQuery, Databricks, Vertex AI, Sagemaker)
- Metrics & Process: DevSecOps performance metrics e.g. strong background with DORA Metrics and other relevant performance indicators Being open to different points of view is important for our business and the communities we serve. At HSBC, we're dedicated to creating diverse and inclusive workplaces - no matter their gender, ethnicity, disability, religion, sexual orientation, or age. We are committed to removing barriers and ensuring careers at HSBC are inclusive and accessible for everyone to be at their best. We take pride in being a Disability Confident Leader and will offer an interview to people with disabilities, long term conditions or neurodivergent candidates who meet the minimum criteria for the role. If you have a need that requires accommodations or changes during the recruitment process, please get in touch with our Recruitment Helpdesk: Email: hsbc.recruitmenthsbc Telephone:
- Experience: Demonstrable experience in data science, showing strong expertise in data processing, advanced analytics, and model development
- Expertise in SQL and statistical programming languages (e.g., Python, R), coupled with a deep understanding of data modelling principles
- Mastery of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and their application in complex problem domains
- Extensive experience with MLOps principles and tools for model deployment, monitoring, versioning, and lifecycle management
- Proven experience with analytics and visualisation toolkits such as Qlik, Looker, or similar platforms along with Basic API skills (e.g., Postman) for integration and data ingestion
- Proficiency with the latest AI technology stack and practical experience with generative AI applications, including prompt engineering and fine-tuning
- Strong experience with cloud platforms (e.g., GCP, AWS, Azure) and their data/ML services (e.g., BigQuery, Databricks, Vertex AI, Sagemaker)
- Metrics & Process: DevSecOps performance metrics e.g. strong background with DORA Metrics and other relevant performance indicators
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