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This role is based in India and as such all normal working days must be carried out in India.
Join us as a Data Scientist
- We’ll look to you to evaluate and improve the business processes and products using scientific rigour and statistical methods
- This is an opportunity to participate in the data scientist community to identify and deliver opportunities to support the bank’s strategic direction through better use of data
- Gain valuable exposure and hone your expertise as you advance your career in this challenging role
What you'll do
As a Data Scientist, you’ll be supporting and collaborating with multi-disciplinary teams of data engineers and analysts on a wide range of business problems including the prevention of financial crime, understanding customer interactions with the bank and the management of credit risk.
You’ll also be:
- Identifying and working with data sets from across the bank’s data estate to solve difficult, non-routine analysis problems
- Applying advanced analytical methods as needed, typically as part of a team to support wider decision making
- Developing your knowledge of data structures and metrics, advocating for changes where needed for product development
- Conducting analysis that includes data gathering and requirements specification in collaboration with business stakeholders
The skills you'll need
To succeed in this role, you’ll need experience with statistical software, database languages, big data technologies and cloud environments, along with experience articulating and translating business questions and using statistical techniques. You’ll also hold a degree in a quantitative discipline or equivalent practical experience in a data analysis related field.
Additionally, you’ll demonstrate:
- The ability to demonstrate self-direction and motivation and willingness to learn new techniques
- Effective written and verbal communication skills
- Experience working as part of a multidisciplinary team
- Expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models and sampling methods
- Experience in deploying machine learning models into a production environment