Data Scientist at Barclays — Gurugram

Data Scientist at Barclays, Gurugram sits within the Decision Intelligence team — worth knowing this specific team name, since Barclays runs multiple differently-scoped “Data Scientist” postings across different business areas (Controls, Risk, Decision Intelligence), and the actual work, seniority, and reporting line can vary meaningfully depending on which one you’re looking at.

What the Decision Intelligence team actually does

This team drives strategic business impact through advanced analytics, machine learning, and data science — developing predictive models, forecasting solutions, and analytical frameworks that shape customer, risk, and commercial decisions across Barclays. Data Scientists here translate business challenges into scalable analytical solutions, working closely with business, technology, and risk stakeholders to improve operational efficiency and strengthen risk management.

What the role actually involves

• Identifying, collecting, and extracting data from various internal and external sources
• Performing data cleaning, wrangling, and transformation to ensure data quality and analysis-readiness
• Developing and maintaining efficient data pipelines for automated data acquisition and processing
• Designing and conducting statistical and machine learning models to analyze patterns, trends, and relationships
• Developing and implementing predictive models to forecast outcomes and identify risks and opportunities
• Collaborating directly with business stakeholders to identify where data science can genuinely add value

Required experience

• Strong programming skills in Python and SQL
• Experience developing and deploying machine learning models, covering both supervised and unsupervised learning techniques
• Strong understanding of statistical analysis, experimentation, and predictive modeling
• Experience working with large, complex, and diverse datasets — including data preparation, feature engineering, and model optimization
• Familiarity with cloud-based analytics platforms, particularly AWS or equivalent environments
• Knowledge of software engineering and MLOps principles — version control, testing, and deployment practices

What genuinely strengthens an application

• Experience with Spark/PySpark and distributed data processing frameworks — called out as advantageous, not mandatory
• Ability to translate business challenges into analytical solutions and communicate technical concepts clearly to non-technical audiences
• Strong stakeholder management skills, with genuine confidence to constructively challenge and guide decision-making using data
• A commercial mindset genuinely focused on measurable business impact, not just technical elegance
• Real curiosity and a continuous learning mindset

What Barclays Gurugram actually offers

Barclays’ campuses provide modern workspaces, wellness rooms, on-site cafeterias, fitness centers, and collaborative meeting spaces — genuinely comprehensive facilities rather than a bare-bones office. The company also emphasizes structured hybrid working with clearly defined onsite “anchor days,” rather than fully remote or fully in-office arrangements.

A genuinely useful safety note from Barclays itself

As with Barclays’ other listings, the careers page includes a direct, prominent fraud warning — worth sharing with readers given how often large, recognizable banking names get used in recruitment scams targeting data and tech candidates specifically.

Questions Candidates Commonly Have

1. Is this the same seniority level as other “Data Scientist” postings at Barclays? Not necessarily — this posting’s own JD uses “Analyst Expectations,” while other Barclays Data Scientist listings (even in Gurugram) have used AVP-level expectations instead. Always check the specific expectations section in each posting rather than assuming seniority from the title alone.

2. Is remote work an option for this role? No — Barclays describes this as hybrid working with structured, fixed “anchor” onsite days determined by the business area, not fully remote.

3. Is Spark/PySpark experience mandatory to apply? No — it’s explicitly listed as advantageous, not a core requirement. Strong Python, SQL, and machine learning fundamentals are the baseline expectation.

4. Why do salary figures for “Data Scientist at Barclays” vary so dramatically across sources? Different platforms sample different populations — Levels.fyi’s data skews toward senior, more experienced submitters, while Glassdoor’s broader dataset likely better reflects the actual Analyst-level range this specific posting falls into. Confirm the actual offer directly with Barclays rather than anchoring to either extreme.