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Posted 10 days ago
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Role at a glance
You will
Identify, collect, and extract data from various sources, including internal and external sources.
Develop and maintain efficient data pipelines for automated data acquisition and processing.
Design and conduct statistical and machine learning models to analyse patterns, trends, and relationships in the data.
Must-have skills
AWSMachine LearningPythonSQL
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Job description
Location: Gurugram, DLF Downtown Department: Data Science
We are seeking a Data Scientist to join our Decision Intelligence team at Barclays, where you will apply advanced analytics, statistics, and machine learning to solve complex business challenges.
The purpose of this role is 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
Identify, collect, and extract data from various sources, including internal and external sources.
Perform data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
Develop and maintain efficient data pipelines for automated data acquisition and processing.
Design and conduct statistical and machine learning models to analyse patterns, trends, and relationships in the data.
Develop and implement 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.
Analyst Expectations
Meet the needs of stakeholders/customers through specialist advice and support.
Perform prescribed activities in a timely manner and to a high standard.
Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to.
Build relationships with stakeholders/customers to identify and address their needs.
Requirements
Strong programming skills in Python and SQL.
Experience developing and deploying machine learning models, including supervised and unsupervised learning techniques.
Strong understanding of statistical analysis, experimentation, and predictive modelling.
Experience working with large, complex, and diverse datasets.
Familiarity with cloud-based analytics platforms such as AWS or equivalent cloud environments.
Desirable skills
Ability to translate business challenges into analytical solutions and communicate technical concepts to non-technical audiences.
Strong stakeholder management and influencing skills.
Commercial mindset with a focus on delivering measurable business impact and customer value.
This page is for Indian job seekers preparing for cloud engineer, DevOps, backend and solutions architect roles that list AWS as a skill, whether you are a fresher with a first certification or an experienced engineer moving into a senior role. It covers 60 questions in three levels: core services and concepts, then design and configuration choices for one to three years of experience, and finally scenario, security, cost and troubleshooting questions asked in senior rounds. Read each answer, explain it aloud in your own words, and try the CLI commands in a practice account with a billing alert set.
Questions you may be asked
What is the difference between an AWS Region and an Availability Zone?
Explain the AWS shared responsibility model.
What is Amazon EC2, and how do you read an instance type name like m7g.large?
What is Amazon S3, and what are its main storage classes?
