Join us as a “Data Scientist - QA Automation”, within the Controls Analytics and Insight team, supporting the Chief Controls Office function.

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 a “Data Scientist - QA Automation”, you should have experience with:

Basic/ Essential Qualifications
- Creative solutioning skills – able to formulate and execute a strategy where a playbook may not exist.
- Experience in influencing senior stakeholders; you should be as comfortable contributing to a “business meeting” as a technical one. You will be the key person in translating business requirements into technical plans and delivering results back into the business.
- Experience training end users in data science and analytics technologies
- Experience on Python, SQL, and strong ability to work with large and complex data.
- Hands-on experience on supervised/unsupervised models,



along with Model design, deployment and optimization.

Desirable Skillsets/ Good To Have
- Recognised degree/ certification in STEM discipline
- Experience working with Spark, Alteryx, Tableau/Power BI and Cloud based platform.
- Strong verbal and written communication skills, and ability to interface with Business and CCO teams.

This role will be based out of Gurugram.

Purpose of the role
To use creative 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.
- Developme

📌 Data Scientist (Gurugram)
🏢 Barclays
📍 Gurugram