Business Analytics Analyst - Pyspark

Citigroup; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Citi in Bengaluru seeks an analytics professional to own end-to-end marketing analytics using SQL, Python, PySpark, and SAS on large datasets within enterprise data warehouses.

You will translate insights into actionable recommendations for Marketing, Risk and Product, and build recurring dashboards while mentoring junior analysts in a fast-paced, regulated environment.

Qualifications

• 5-7 years of hands-on analytics experience in banking/financial services.
• Strong foundation in consumer banking/product metrics and portfolio economics.
• Experience translating data insights into business recommendations.

Responsibilities

• Design and execution of test-vs-control and uplift campaigns for marketing analytics.
• Build and maintain dashboards/scorecards for campaign monitoring and post-campaign readouts.
• Collaborate with Marketing, Risk, Finance and Tech teams to implement insights.

Skills

SQL

Python

PySpark

SAS

Job description

Technical / Tools Proficiency

• SQL : Advanced querying (joins, window functions, CTEs, performance tuning) across large relational/Teradata/Hive data warehouses.
• Python : Data wrangling (pandas/numpy), automation scripting, statistical analysis, and visualization (matplotlib/seaborn).
• PySpark : Distributed data processing for large campaign/transaction datasets, working within Hadoop/Spark ecosystems.
• SAS : Base SAS and SAS Macros for large-scale data manipulation, campaign tagging, and reporting automation.

Domain Knowledge - Banking & Card Products

• Solid grounding in consumer banking/credit card business fundamentals: account lifecycle, interest income, fees, credit risk basics, and portfolio economics.
• Understanding of the credit card marketing lifecycle: acquisition, activation, usage, retention, and attrition.

Campaign Analytics & Measurement

• Design and execution of test-vs-control and champion-challenger frameworks for campaign effectiveness.
• Incrementality/lift analysis, response modeling, and uplift measurement.
• Campaign performance tracking: response rates, conversion, activation, spend, and profitability metrics.
• Experience building recurring performance dashboards/scorecards for campaign monitoring and post-campaign readouts.

Statistical & Quantitative Analysis

• Hypothesis testing, A/B testing methodology, and significance testing.
• Segmentation and targeting analysis (behavioral, demographic, risk-based).
• Regression/predictive modeling exposure (logistic regression, decision trees) for propensity/response scoring is a plus.
• Data quality checks, reconciliation, and root-cause/variance analysis.

GenAI / Emerging Tools Familiarity

• Working knowledge of Generative AI tools for analytics productivity - e.g., using LLM-based assistants for code generation/debugging (SAS/SQL/Python), documentation, and summarization of campaign results.
• Exposure to prompt engineering basics for querying enterprise GenAI platforms (e.g., internal chat/assist tools) to accelerate exploratory analysis and reporting.
• Awareness of GenAI use cases in marketing analytics: automated insight generation, natural-language querying of datasets and synthetic test data creation.
• Curiosity/adaptability to continuously evaluate and adopt new AI-assisted analytics tools as the function modernizes its toolkit.

Communication

• Ability to translate analytical findings into actionable business recommendations for marketing/product stakeholders.
• Strong storytelling with data - clear presentation of insights to senior stakeholders (PowerPoint/Excel proficiency).
• Cross-functional collaboration with Marketing, Risk, Finance, and Technology teams.
• Project management skills to manage multiple concurrent campaign analytics requests under tight timelines.

Behavioral Attributes

• Independent ownership of analytics workstreams with minimal supervision, commensurate with 5-7 years of hands-on experience.
• Mentoring junior analysts and reviewing their analytical output.
• Strong attention to detail and controls mindset given regulatory sensitivity of rate-based offers.
• Proactive problem-solving and ability to work in ambiguous, fast-paced environments.
• Experience Level: 5-7 years of relevant analytics experience, preferably in banking/cards/financial services.

Job Family Group: Decision Management

Job Family: Business Analysis

Time Type: Full time

Most Relevant Skills: Please see the requirements listed above.

Other Relevant Skills: For complementary skills, please see above and/or contact the recruiter.

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