# Associate Analyst, Analytics & Metrics **Company**: Mastercard **Location**: Navi Mumbai, India **Experience**: mid **Job type**: full-time **Category**: Data Science **Industry**: Finance **Apply**: https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Navi-Mumbai-India-Finicity/Associate-Analyst--Analytics---Metrics_R-293135?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_e409a254-5f7 ## Description We are seeking a Data Analyst to transform complex payments, transaction, customer, and operational data into accurate reporting and actionable business insights. The role combines hands-on data management, data quality, SQL and Python analysis, dashboard development, reporting automation, and stakeholder collaboration. **Responsibilities** - Data Preparation, Quality and Governance: - Extract, compile, cleanse, validate, standardize, and organize large datasets from multiple internal and external sources using SQL, Python, Excel, and approved data platforms. - Review data for completeness, accuracy, consistency, duplication, and compatibility; investigate discrepancies and correct issues where possible or escalate them through defined channels. - Research and obtain missing information required to complete datasets, records, or supporting documentation. - Apply defined data extraction, labelling, categorization, mapping, reconciliation, and quality-control procedures. - Perform internal quality reviews and maintain clear evidence of checks, corrections, assumptions, and data lineage. - Handle sensitive and confidential information with professional maturity and comply with applicable data privacy, security, governance, and retention requirements. - Analysis and Business Insights: - Analyze payments and transaction data to identify trends, anomalies, customer behavior, operational performance, and potential growth or efficiency opportunities. - Use descriptive statistics, trend analysis, segmentation, model testing, and root-cause analysis. - Translate business requirements into structured analytical approaches, datasets, metrics, and reporting solutions. - Interpret findings with the end user in mind and provide clear, practical recommendations supported by data. - Collaborate with business, operations, product, risk, and technology stakeholders to clarify requirements and validate analytical outputs. - SQL, Python, Databricks and Automation: - Write and optimize SQL queries using joins, common table expressions, subqueries, aggregations, and window functions for extraction, validation, reconciliation, and analysis. - Use Python, particularly pandas and NumPy, to manipulate data, perform quality checks, conduct analysis, and build reusable processing scripts. - Work with Databricks notebooks and Spark or PySpark for data preparation and distributed processing, with guidance for more complex engineering activities. - Automate recurring reports, validation routines, and data preparation processes to reduce manual effort and improve consistency. - Support basic machine-learning activities such as feature preparation, model testing, performance evaluation, classification, clustering, or predictive analysis under established frameworks. - Document code, logic, dependencies, business rules, and operating procedures so solutions can be reviewed, maintained, and reused. - Reporting and Visualization: - Build, maintain, and enhance dashboards in Power BI, Tableau, or similar tools to track business metrics, KPIs, trends, and exceptions. - Prepare accurate recurring and ad-hoc reports, presentations, and analytical summaries for technical and non-technical audiences. - Validate dashboard calculations and reporting outputs against source systems before release. - Store completed work in designated repositories, maintain appropriate versions, and perform backup activities as instructed. - Present findings, limitations, and recommendations clearly to stakeholders and respond to follow-up questions with supporting evidence. - Delivery and Collaboration: - Manage multiple assignments or projects simultaneously while meeting agreed quality, productivity, and turnaround expectations. - Work effectively in a fast-paced environment, prioritize competing requests, and communicate risks or delays early. - Partner with cross-functional and global teams, participate in reviews, and contribute to process and reporting improvements. - Operate independently on defined tasks while seeking appropriate guidance for complex, ambiguous, or high-risk issues. - Demonstrate professionalism, accountability, punctuality, attention to detail, and a goal-oriented approach. **Requirements** - Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Engineering, Data Science, Commerce, or a related discipline. - 3-4 years of experience in data analytics, business intelligence, data management, reporting, or a related technical role. - Proven experience working with large datasets, performing data validation, resolving quality issues, and delivering accurate analytical outputs. - Strong SQL skills, including joins, aggregations, common table expressions, window functions, and complex queries. - Proficiency in Python for data manipulation and analysis, particularly pandas and NumPy. - Good to have knowledge on Power BI, Tableau, or a comparable data-visualization platform. - Good Microsoft Excel skills, including formulas, pivot tables, lookups, data analysis, and preferably Power Query. - Working knowledge of statistics, trend analysis, model testing, and analytical problem-solving. - Excellent written and verbal communication skills, including report writing, presentations, and stakeholder discussions. - Strong organizational and time-management skills, with the ability to manage priorities and deliver work accurately within deadlines. - Experience with web-based applications, internet research, Microsoft Office, and common data-management tools. ## Skills ### Required - SQL - Python - Data Analysis - Statistics - Data Visualization - Power BI - Tableau - Microsoft Excel - Databricks - Spark - PySpark ### Nice to have - Experience in payments, banking, fintech, financial services - Familiarity with payment and transaction metrics - Exposure to machine-learning modelling - APIs - Git or version control - reporting automation - A/B testing - predictive analytics --- Source: [Apply at mastercard.wd1.myworkdayjobs.com](https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Navi-Mumbai-India-Finicity/Associate-Analyst--Analytics---Metrics_R-293135?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)