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Barclays

Data Scientist

Barclays is hiring a Data Scientist in Gurugram, India. Level rates it ; you can apply on Barclays.

Level's read on this job

  • Level rates this data scientist role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions Python, SQL and MLOps among its tools and skills.
  • Level classes it as a mid-level role.
  • Barclays has 607 other open roles on Level.

AI in this role

Develop machine learning and predictive models to extract insights and drive data-driven decision making across the bank.

PythonSQL
ml-opsmachine-learningstatistical-modelingpredictive-modelingdata-pipelinesdata-wrangling
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.

Analyst Expectations

  • To meet the needs of stakeholders/ customers through specialist advice and support
  • Perform prescribed activities in a timely manner and to a high standard which will impact both the role itself and surrounding roles.
  • Likely to have responsibility for specific processes within a team
  • They may lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. They supervise a team, allocate work requirements and coordinate team resources.
  • 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 manage own workload, take responsibility for the implementation of systems and processes within own work area and participate on projects broader than direct team.
  • Execute work requirements as identified in processes and procedures, collaborating with and impacting on the work of closely related teams.
  • Check work of colleagues within team to meet internal and stakeholder requirements.
  • Provide specialist advice and support pertaining to own work area.
  • Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
  • Maintain and continually build an understanding of how all teams in area contribute to the objectives of the broader sub-function, delivering impact on the work of collaborating teams.
  • Continually develop awareness of the underlying principles and concepts on which the work within the area of responsibility is based, building upon administrative / operational expertise.
  • Make judgements based on practise and previous experience.
  • Assess the validity and applicability of previous or similar experiences and evaluate options under circumstances that are not covered by procedures.
  • Communicate sensitive or difficult information to customers in areas related specifically to customer advice or day to day administrative requirements.
  • Build relationships with stakeholders/ customers to identify and address their needs.

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 will apply advanced analytics, statistics and machine learning to solve complex business challenges. You will work with large-scale datasets to develop predictive models, create CI/CD pipelines, generate actionable insights and support strategic decision-making across customers, risk and commercial domains.

The Decision Intelligence team at Barclays drives strategic business impact through advanced analytics, machine learning and data science. The team develops predictive models, forecasting solutions and analytical frameworks that help shape customer, risk and commercial decisions across the business. Working with large and complex datasets, Data Scientists translate business challenges into scalable analytical solutions, uncover actionable insights and support data-driven decision making. The team collaborates closely with business, technology and risk stakeholders to deliver innovative solutions that enhance customer outcomes, improve operational efficiency, strengthen risk management and create measurable commercial value.

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

  • 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, including data preparation, feature engineering and model optimisation.
  • Familiarity with cloud-based analytics platforms such as AWS or equivalent cloud environments.
  • Experience with Spark/PySpark and distributed data processing frameworks is advantageous.
  • Knowledge of software engineering and MLOps principles, including version control, testing and deployment practices.

Desirable skills/ good to have:

  • Ability to translate business challenges into analytical solutions and communicate technical concepts to non-technical audiences.
  • Strong stakeholder management and influencing skills, with the confidence to challenge constructively and guide decision-making using data.
  • Commercial mindset with a focus on delivering measurable business impact and customer value.
  • Strong problem-solving skills, curiosity and a continuous learning mindset.
  • We're looking for someone who combines strong analytical and technical capabilities with the ability to work collaboratively across teams. The ideal candidate is passionate about solving real-world business problems, enjoys working with data at scale, and is motivated by delivering outcomes that create meaningful value for customers and the organization.

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

Location - Gurugram.

How we rate this

Data Scientist at Barclays rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsMachine learningStatistical ModelingPredictive ModelingData PipelinesData WranglingPythonSQL

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$168k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where statistical modeling was part of your work. What did you do?
  4. Tell me about a project where predictive modeling was part of your work. What did you do?
  5. Tell me about a project where data pipelines was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: ML Ops, Machine learning, Statistical Modeling, Predictive Modeling, and Data Pipelines. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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