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Data Analyst, Python, SQL and SAS

Citigroup

  • Bengaluru, Karnataka, India
  • β‚Ή8-12 LPA
  • Fresher (0-1 Yrs)
  • Posted Today
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About the role

Citi is a global financial services powerhouse with a presence in more than 160 countries and a workforce of over 219,000 professionals. The bank offers a broad range of services including consumer banking, corporate and investment banking, securities, and wealth management. Known for its strong emphasis on innovation, Citi invests heavily in technology and data-driven solutions to stay ahead in a rapidly evolving financial landscape.

The company’s culture promotes diversity, inclusion, and continuous learning, providing employees with opportunities to work on high‑impact projects that shape the future of finance.

The Data Analyst role in Bengaluru is an entry‑level position within the Data/Information Management team. As a Data Analyst, you will support senior analysts and business partners by extracting, cleaning, and interpreting large data sets using SQL, Python, and SAS. You will translate business requirements into analytical solutions, create automated reports, and help drive data‑centric decision making across the organization.

This hybrid role blends technical rigor with strong communication skills, allowing you to interact with stakeholders from various functions while honing your analytical expertise.

Key Responsibilities

  • Retrieve, manipulate, and analyze data from relational databases using SQL, Python, and SAS.
  • Replicate and adapt existing analytical models and reports for new markets or business segments.
  • Produce, validate, and enhance recurring management reports, dashboards, and scorecards.
  • Identify automation opportunities and develop scripts or workflows to reduce manual effort.
  • Collaborate with business stakeholders to gather requirements and ensure deliverables meet expectations.
  • Prepare clear presentations and executive summaries that convey insights and recommendations.
  • Maintain data governance standards, documentation, and control procedures.
  • Participate in continuous improvement initiatives, suggesting enhancements to data pipelines and reporting processes.
  • Support ad‑hoc analytical requests and deep‑dive investigations as needed.
  • Stay updated with emerging tools and best practices in data analytics and visualization.

Tech Stack: SQL, Python, SAS, Tableau (nice to have), Dataiku (nice to have), Excel, PowerPoint.

Growth Path: Starting as a Data/Information Management Analyst 2, high performers can progress to Senior Analyst, Lead Analyst, and eventually to Manager or Data Product Owner roles, with exposure to global finance projects and cross‑functional leadership opportunities.

Why Join Citi: Citi offers a structured early‑career program, mentorship from industry veterans, and a global platform to work on real‑world financial data. The hybrid work model provides flexibility, while the company’s commitment to learning ensures you acquire cutting‑edge analytical skills. Competitive compensation, robust benefits, and a culture that values diversity make Citi an attractive launchpad for aspiring data professionals.

Eligibility & process

Who can apply

Bachelor's or Master's degree in Computer Science, Information Technology, Statistics, Mathematics, Economics or related fields; 60% or above in aggregate; graduating batch 2024‑2026; no active backlogs at the time of joining; strong analytical mindset and willingness to learn new tools.

Skills & stack

SQL Python SAS Tableau Dataiku Data Cleaning Data Visualization Presentation Skills

Selection process

  1. Round 1: Online aptitude test (logical reasoning, quantitative, verbal)
  2. Round 2: Technical interview (SQL, Python, SAS, case studies)
  3. Round 3: HR interview (behavioral fit, career aspirations)

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (SQL, Python, SAS, Tableau, Dataiku, Data Cleaning, Data Visualization, Presentation Skills) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Citigroup Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Citigroup as a Data Analyst, Python, SQL and SAS?
Highlight Citigroup's market reputation, recent tech innovations, and how your skills in SQL directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Citigroup β‚Ή8-12 LPA
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