Data Analyst
@ METRO/MAKRO

Pune, Maharashtra, India
₹800,000
On Site
Full-time
Posted 8 hours ago

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Job Details

About the Role

The Data Analyst will build and maintain dashboards, conduct deep data analysis, and lead experimentation practices for a heavy ML-driven product at Metro Global Solution Center (MGSC). The role involves collaborating with product teams to drive data-driven decisions and improve KPIs for international operations.

Key Responsibilities

  • Build and maintain dashboards for KPI tracking.
  • Dig into data to uncover new use cases.
  • Lead the team’s experimentation practice.
  • Identify and resolve data quality issues.
  • Collaborate with product teams and stakeholders.
  • Develop new KPIs as needed.
  • Educate teams on data usage.

Qualifications

Applicants should hold a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related fields along with strong analytical, communication, and technical skills.

Technical Skills

  • Advanced SQL and query optimization (BigQuery preferred).
  • Experience with dashboarding tools such as Looker Studio, Microstrategy, Tableau, or Looker.
  • Proven A/B testing experience including experiment design and statistical evaluations.
  • Proficiency in Python, particularly using Jupyter notebooks.
  • Solid understanding of Git version control.

Nice-to-Have

  • Experience in cross-functional collaboration.
  • Understanding of recommender systems.
  • Experience with Google Cloud Platform analytical technologies.

Key skills/competency

Data Analysis, SQL, Dashboarding, Python, A/B Testing, Statistics, Data Quality, Experimentation, Collaboration, Git

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How to Get Hired at METRO/MAKRO

🎯 Tips for Getting Hired

  • Research Metro/MAKRO's culture: Explore the company's mission and projects.
  • Tailor your resume: Highlight SQL, Python, and dashboarding skills.
  • Prepare data experiments: Showcase A/B testing and statistical analysis.
  • Demonstrate collaboration: Provide examples working with cross-functional teams.

📝 Interview Preparation Advice

Technical Preparation

Review advanced SQL queries.
Practice Python analysis in Jupyter.
Study dashboarding tool functionalities.
Brush up on statistical testing methods.

Behavioral Questions

Describe handling challenging data issues.
Explain collaboration with cross-functional teams.
Share a successful experiment story.
Discuss adapting to feedback quickly.

Frequently Asked Questions