Website Mastercard
Associate Analyst, Analytics & Metrics — Mastercard
Company: Mastercard
Role Title: Associate Analyst, Analytics & Metrics
Location: Navi Mumbai, Maharashtra, India
Work Mode: Hybrid / Office-Based (Flexibility to support rotational shifts / US holiday calendar alignment where required)
Employment Type: Full-Time
Experience Level: 3 to 4 Years of professional experience in data analytics, business intelligence, data management, or financial reporting
Educational Requirement: Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering, Data Science, Commerce, or a related discipline
Core Tool Stack: SQL (Advanced), Python (Pandas, NumPy), Databricks, Spark / PySpark, Advanced Excel,Power BI / Tableau
Preferred Industry: Payments, Banking, Fintech, Financial Services, or Transaction-Intensive Environments
About Mastercard
Mastercard is a leading global technology company powering the digital economy and connecting economies across more than 200 countries and territories. Mastercard makes transactions secure, simple, smart, and accessible through innovative digital payments technology, advanced data analytics networks, and fraud prevention architectures. Mastercard’s technology hub in Navi Mumbai drives core business intelligence, operational analytics, transaction processing security, and merchant growth metrics.
Role Overview
Mastercard is recruiting a meticulous and technically skilled Associate Analyst, Analytics & Metrics for its office in Navi Mumbai.
In this role, you will transform complex payments, transaction, customer, and operational datasets into accurate business reporting and actionable strategic insights. You will manage end-to-end data preparation, governance, and quality controls, write advanced SQL and Python processing scripts, build Databricks workflows, design executive visualisation dashboards, and partner with cross-functional global teams.
Key Responsibilities
Data Preparation, Quality & Governance
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Data Cleansing & Extraction: Extract, compile, cleanse, validate, standardize, and organize massive multi-source datasets using SQL, Python, Excel, and approved corporate platforms.
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Data Integrity & Reconciliation: Review data completeness, consistency, and duplication; investigate discrepancies, obtain missing records, and apply rigorous quality-control rules.
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Compliance & Lineage: Maintain clear documentation of data checks, lineage, assumptions, and corrections while strictly adhering to data privacy, security, and governance standards.
Analytics & Business Insights
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Transaction Analytics: Analyze payments and transaction flows to identify emerging trends, customer behavior patterns, operational efficiencies, and growth opportunities.
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Descriptive & Root-Cause Analysis: Apply descriptive statistics, trend analysis, customer segmentation,and root-cause troubleshooting to answer business queries.
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Stakeholder Alignment: Translate business inquiries into structured analytical approaches and deliver practical, data-backed recommendations to product, risk, and operations teams.
SQL, Python, Databricks & Automation
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SQL Optimization: Write and optimize complex SQL queries utilizing joins, aggregations, common table expressions (CTEs), subqueries, and window functions.
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Python Manipulation: Use Python (pandas and NumPy) for data manipulation, quality validation,analytical modeling, and reusable processing script creation.
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Databricks & Spark: Leverage Databricks notebooks and Spark / PySpark for distributed data preparation and scaling.
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Reporting Automation: Automate recurring validation routines and data preparation pipelines to eliminate manual operational effort.
Reporting & Visualization Dashboards
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Dashboard Engineering: Build, maintain, and enhance executive dashboards in Power BI, Tableau, or comparable BI tools to monitor KPIs and transaction exceptions.
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Ad-Hoc Summaries: Prepare accurate recurring and ad-hoc reports, presentations, and analytical summaries for technical and non-technical stakeholders.
Candidate Qualifications & Requirements
Required Qualifications & Experience
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Education: Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering,Data Science, Commerce, or a related quantitative/analytical discipline.
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Experience: 3 to 4 years of hands-on experience in data analytics, business intelligence, data management, or financial reporting.
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Technical Mastery:
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Advanced SQL skills (joins, aggregations, CTEs, window functions).
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Strong Python proficiency for data manipulation (pandas, NumPy).
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Solid Microsoft Excel skills (formulas, pivot tables, VLOOKUP/XLOOKUP, Power Query).
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Communication: Exceptional written and verbal communication skills for stakeholder discussions,technical report writing, and presentations.
Preferred Qualifications
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Experience within payments, banking, fintech, or transaction-intensive environments.
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Familiarity with payment transaction metrics, fraud/anomaly detection, and operational analytics.
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Exposure to Databricks, Spark, PySpark, Delta tables, or cloud data platforms.
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Exposure to machine learning modeling (feature engineering, model evaluation, classification/clustering) and API integrations.
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Relevant professional certifications in analytics, cloud platforms, Python, SQL, or Databricks.
Role Summary
| Attribute | Details |
| Job Title | Associate Analyst, Analytics & Metrics |
| Company | Mastercard |
| Location | Navi Mumbai, Maharashtra, India |
| Experience | 3–4 Years |
| Primary Skill Stack | SQL, Python (Pandas/NumPy), Databricks, Spark/PySpark, Excel, Power BI / Tableau |
| Core Focus | Data Governance, Payments Analytics, Automated Reporting Pipelines, Executive Visualization |
