Mastercard Hiring Data Analyst - Work From Home / Hybrid

Mastercard Data analyst jobs Drive :-

Mastercard Hiring Data Analyst – Work From Home / Hybrid

Mastercard, a leader in driving a secure and inclusive digital economy, is hiring an entry-level data analyst jobs in Analytics & Metrics for its Pune, Maharashtra office. This hybrid role involves creating innovative data-driven solutions to power business decisions and foster long-term client relationships. By joining our GBSC Analytics and Metrics team, you will be an integral part of Mastercard’s mission to connect people to priceless possibilities. If you’re passionate about data, problem-solving, and visualization, this could be the ideal fit for you!

Overview

Job Position: Analyst, Analytics & Metrics
Job Location: Pune, Maharashtra, India (Hybrid)
Salary Package: As per Company Standards
Full/Part Time: Full Time
Req ID: R-232047
Education Level:Bachelor’s degree / Any Graduation
Company Website: www.mastercard.com

Explore an exciting entry-level opportunity with Mastercard in Pune as an hybrid data analyst jobs in Analytics & Metrics. Join our team to leverage your analytical skills and data expertise in a role that involves data automation, visualization, and strategic insights. Grow with us in a hybrid role that values creativity and collaboration.

If You match the qualifications ,skills and comfirtable working with the given roles and responsibilities then your are ready to get this hybrid data analyst job in pune please read this job post till the end to get your next job and check the remote jobs page of kaabiljobs to know more remote data analyst jobs. all the best for your interview

Qualifications

Educational Background: Bachelor’s degree in Computer Science, Data Analytics, Statistics, or a related field.
Certifications: Preferred certifications in Power BI or Tableau; certifications in Alteryx and SQL are a plus.
Experience: Knowledge of data visualization techniques, statistical analysis, and reporting.
Programming Skills: Familiarity with Python or R for data manipulation, and experience with SQL for managing complex queries.
Soft Skills: Excellent problem-solving, communication, and collaborative skills for a team-oriented environment.

Roles and Responsibilities

Data Visualization & Dashboarding: Use Tableau and Power BI to create intuitive dashboards that clearly communicate data insights and trends.
Data Automation: Design automated solutions using Alteryx to streamline processes and support Mastercard’s global operations.
Data Integration & Analysis: Develop ETL workflows to integrate data from structured and unstructured sources, enabling comprehensive data analysis.
Stakeholder Collaboration: Work closely with cross-functional teams to define and align data objectives that support Mastercard’s strategic goals.
Documentation & Communication: Prepare presentations and reports to effectively convey insights and findings to both technical and non-technical audiences.

Skills Required

Technical Skills:
- Data Automation: Proficient in Alteryx for data preparation and workflow automation.
- Data Visualization: Skilled in Tableau and Power BI, adhering to best practices in dashboard creation.
- SQL: Strong knowledge of SQL, including optimization and troubleshooting.
- Data Modeling: Familiarity with data modeling concepts and techniques.
- Power Platform Knowledge: Experience with Power Apps and Power Automate.
Soft Skills:
- Analytical mindset with a strong problem-solving orientation.
- Ability to communicate technical insights to a non-technical audience.
- High attention to detail with a focus on quality and accuracy in data reporting.
- Collaborative spirit to work effectively within cross-functional teams.

Job Description:-

As an Analyst in the GBSC Analytics & Metrics team, you’ll transform raw data into strategic insights that shape Mastercard’s global initiatives. Your primary responsibilities will involve developing data automation workflows, creating visual reports, and building dashboards to answer critical business questions. This role provides an excellent opportunity for you to showcase your analytical skills, creativity, and ability to drive actionable insights using data.

Mastercard Data analyst Recruitment Drive Application Process:-

Apply In Below Link

Apply Link:- Click Here To Apply (Apply before the link expires)

Click Here To Apply

Share This Job Post

Join Us For Regular Job Updates

Related Jobs

Interview Preparation Tips

Understand Data’s Role in Business – Review how data analytics drives Mastercard’s decision-making.
Hands-On Practice – Bring real-world examples of data projects using Tableau, Alteryx, or SQL.
Prepare to Tell a Data Story – Practice clear communication of insights to both technical and non-technical audiences.
Be Ready for Technical Scenarios – Expect questions that test your creativity and analytical mindset.
Showcase Problem-Solving Skills – Highlight resourcefulness in tackling data challenges.

Share This Tips

Here’s a list of study resources to help you get interview-ready:

Tableau & Power BI Guides – Focus on dashboard development best practices.

Alteryx Essentials – Master ETL processes and automation workflows.

SQL Optimization Techniques – Review complex queries and learn performance tuning.

Python for Data Analysis – Practice data manipulation and basic machine learning applications.

Data Visualization Techniques – Gain insights on data storytelling for business impact.

Get Personalized Interview Preparation Services

Need personalized preparation? Kaabil Jobs offers comprehensive services, including mock interviews, tailored study plans, and expert guidance to help you succeed in your Interviews.
Get started today and boost your chances of landing the job!

Join Us For Study Material and Job Updates

Common Technical and Non-Technical Interview Questions

If you’re prepping for hybrid data analyst jobs in pune interview, here’s a mix of likely technical and non-technical questions to expect:

How do you automate data workflows in Alteryx, and what business problems have you solved with automation?In my previous role, I used Alteryx to automate data workflows for managing large datasets. For instance, I designed a workflow that automated the process of data cleansing, transformation, and aggregation, reducing the processing time by over 50%. By automating these workflows, I enabled our team to focus more on data analysis and less on manual data preparation, leading to faster and more accurate insights.
Explain your approach to developing an effective dashboard in Tableau. How do you decide what data to display?My approach to creating dashboards in Tableau starts with understanding the needs of stakeholders and the primary questions they aim to answer. I prioritize data that directly supports these questions and apply best practices in visualization to ensure clarity. For example, in a recent project, I created a Tableau dashboard focusing on key performance indicators, using colors and filters strategically to make the data accessible to both technical and non-technical users.
How do you optimize SQL queries to improve performance? Give an example.To optimize SQL queries, I focus on reducing redundant joins, indexing relevant columns, and minimizing data fetched by using specific filters. For example, in a recent project, I optimized a report by indexing high-use columns, which resulted in a 40% faster query execution time. This was particularly useful in real-time data analysis, where speed was essential for effective decision-making.
Describe a complex data integration project. How did you manage data from multiple sources?In my previous role, I led a data integration project that involved merging datasets from SQL databases, flat files, and API sources. Using Alteryx, I created an ETL workflow that cleaned and normalized the data before combining it. This integration process enabled us to deliver comprehensive insights by using unified data, which improved the accuracy and reliability of the analytics.
What is your experience with Power BI’s DAX functions? How have you used them in past projects?I have experience using DAX functions in Power BI to create calculated columns, measures, and custom visuals. For example, I used DAX to calculate rolling averages and year-over-year growth in a sales report. This functionality allowed our stakeholders to see trends over time, which was crucial for strategic planning.
Can you discuss a time when you used Python or R for data analysis?In a previous project, I used Python for sentiment analysis on customer feedback data. Using libraries like Pandas and NLTK, I processed and analyzed the data to identify trends in customer satisfaction. This analysis provided actionable insights, which helped our team improve the customer experience by addressing specific concerns highlighted in the feedback.
Describe a scenario where data visualization helped solve a critical business issue.In one of my projects, we were analyzing churn data for a subscription service. By creating a Power BI dashboard that visualized key metrics, such as user demographics and usage patterns, we identified the main factors contributing to churn. This visualization enabled our team to take targeted actions, like enhancing features for high-churn segments, which ultimately reduced churn by 15%.
What are some best practices you follow for data modeling in analytics projects?I ensure data models are efficient and maintainable by normalizing tables, indexing key columns, and avoiding unnecessary joins. Additionally, I document relationships and assumptions, so future updates or changes are streamlined. This approach enhances performance, making it easier to scale the model for large datasets.
How would you handle a data quality issue while working on a critical project?I would address data quality issues by first analyzing the scope and identifying the root cause. Then, I’d communicate with stakeholders to assess the impact. In one project, I encountered missing data in critical fields. I addressed this by setting validation rules and using Alteryx to automate quality checks, which helped maintain data integrity in future analyses.
Explain how you would approach creating an interactive dashboard for non-technical users.For non-technical users, I create dashboards that are visually intuitive and easy to navigate, using simple charts, color coding, and minimal technical jargon. I often include tooltips to provide additional context and ensure that the dashboard is interactive so users can filter views based on their needs.

Join Us For More Technical Questions and Job Updates

Describe a challenging data project and how you overcame obstacles during its execution.In one project, we faced challenges with data integration due to inconsistent data formats across sources. I resolved this by standardizing the data using Alteryx workflows, which allowed us to merge the data seamlessly. This approach required patience and thorough testing but ultimately led to a unified dataset that supported reliable analytics.
How do you prioritize tasks when managing multiple data projects?I prioritize tasks based on project deadlines, stakeholder needs, and the potential impact of each project. For instance, if one project directly impacts business strategy, I would allocate more time and resources to it. I use task management tools to keep track of progress, ensuring I meet all deadlines.
Tell us about a time you had to explain complex data insights to a non-technical team. How did you approach it?While presenting a data analysis project to a sales team, I focused on simplifying the technical jargon and used visual aids like charts and graphs. I framed insights in terms of business outcomes, such as “This trend indicates a 10% potential increase in sales,” making it relatable and easy to understand.
What’s your method for staying updated on analytics trends and tools?I regularly read industry blogs, attend webinars, and take online courses to stay updated on tools like Alteryx, Tableau, and Power BI. Additionally, I’m part of several analytics communities, where I exchange insights with peers, which helps me stay current with best practices and emerging trends.
How do you ensure accuracy and quality in your reports and dashboards?To ensure accuracy, I validate data at every stage of the ETL process and cross-check results. I also perform regular testing and seek peer feedback to catch any errors before finalizing the report or dashboard. This rigorous approach minimizes mistakes and maintains data reliability.
Can you discuss a time when teamwork led to better outcomes in an analytics project?In a previous project, I collaborated with a cross-functional team to develop a customer segmentation model. Each member brought unique insights, which helped us identify more granular customer segments. This teamwork led to a model that was both robust and actionable, ultimately improving targeting for marketing campaigns.
How would you handle feedback from stakeholders about a visualization you created?I appreciate constructive feedback and view it as an opportunity to improve. In one instance, a stakeholder suggested adding filters to a dashboard for better data segmentation. I implemented their feedback, which made the dashboard more user-friendly and increased its value for decision-making.
Describe a time when you solved a business problem creatively using data.I once worked on a project to optimize resource allocation. By analyzing usage patterns, I identified underutilized resources and reallocated them to high-demand areas. This creative approach saved costs and improved efficiency without needing additional resources.
What do you think is the most important quality for someone working in analytics?The most important quality is analytical curiosity, as it drives one to ask the right questions and dig deeper into data. This curiosity enables analysts to uncover insights that may otherwise be overlooked, which is essential for creating value through data-driven decisions.
How do you handle data confidentiality and security in your work?I follow company protocols and industry standards to protect data confidentiality. This includes using secure storage solutions, limiting data access to authorized personnel, and ensuring compliance with security guidelines. For example, I always anonymize sensitive information when sharing data outside the team to maintain privacy.

Join Us For More Non-Technical Questions and Job Updates

Why Join Mastercard?

As you know mastercard hiring data analyst.At Mastercard, our work is rooted in a strong commitment to creating an inclusive, innovative environment that enables every team member to contribute fully. You’ll be part of a company that values your expertise, encourages your ideas, and supports your growth. With us, you’ll get the opportunity to tackle meaningful challenges and develop cutting-edge solutions, all while working alongside a team that’s dedicated to creating a better future through data. If you’re ready to take your analytics skills to a new level, this role is your gateway.This isn’t just a job; it’s a career launchpad. If you’re passionate about technology and solving meaningful problems, don’t miss this chance to be part of Google. Whether you’re a fresher looking for your first big break or a tech enthusiast ready to dive into large-scale projects, this Software Engineer role is your gateway to making a real difference.

Share Your Software Engineer Interview Experience

Share My Experience

Mastercard Data analyst jobs Drive :-