Job Description

Purpose of the role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation. 

Accountabilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join us as a "Data Scientist" at Barclays, where you'll build analytical tools to generate insight, recognise patterns and predict behaviour, and deliver content direct to users of information products. You will work with technical teams, architects, designers, and administrators to overcome technical challenges and to make it happen. You will need to take ownership of key initiatives to deliver results through an agile workflow. Will have to design, test and build complex forecast models and simulations to identify causal links between customer behaviour and business opportunities and performance.

You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.

To be successful as an "Data Scientist", you should have experience with:

Essential Skills and Qualifications:

• Bachelor or masters degree in data science (or similar) or equivalent commercial experience
• Experience with working with senior stakeholders across the data science life cycle from inception of an idea to the delivery within a production environment
• Ability to translate technical work into business terms and communicate value to business stakeholders.
• Commercial experience in applying machine learning techniques to generate business value (e.g.  clustering, classification, regression, NLP techniques)
• Ability to write close to production standard code with strong understanding of key coding principals e.g. separation of concerns, generalisation of code. Strong experience in Python and SQL is a must.
• Familiarity with AWS data science and AI services, including SageMaker and Bedrock.
• Understanding of GenAI , LLMs and the RAG framework.
• Proficiency in data visualization software, ideally Tableau, with exposure to QlikView, PowerBI, or similar tools.
• Knowledge of code management methodologies and ability to implement these on projects.
  Build relationships with senior stakeholders across the bank to seek out opportunities to add value through Data Science and GenAI.
• Develop machine learning models and apply AI to deliver commercial value for the Corporate Bank.
• Leverage AWS services for data transformation, feature engineering , AI product development and deployment.
• Communicate complex technical ideas to stakeholders via  data visualisation.
• Work closely with our equivalent ML Ops team in technology to streamline the path to production for successful projects.
   

Desirable skills/Preferred Qualifications:

• Experience in front end development frameworks such as Angular/React Flask/Streamlit.
• MVC Architecture.
• Experience of working in a big data environment using PySpark.

This role will be based out of Gurugram.