Kantar Off Campus Drive 2025 hiring Data Analyst Job, Bangalore

Apply for Kantar Off Campus Drive 2025! Hiring Data Analyst Job in Bangalore for BE/BTech/ME/MTech 1-4 years experience in Python, SQL, machine learning, and ETL tools. Transform data into actionable insights in a data science team to improve user engagement.

Candidates who are interested in Kantar Off Campus Drive Job Openings can go through the below to get more information.

Key Job details of Data Analyst jobs

Company: Kantar

Qualifications: BE/BTech/ME/MTech

Experience Needed: 1-4 years

Job Req ID: R087095

Location: Bangalore

Selenium Automation Training

Start Date: 28th July 2025

Click here to Join on WhatsApp:- https://bit.ly/39gGfwZ

Click here to Join on Telegram:- https://telegram.me/qaidea

Job Description

We are seeking candidates with experience in a data-related role, possessing a solid foundation in programming (Python and SQL) and a passion for redefining data into actionable insights. You will join our data science department and work directly with our Senior Data Scientists.

Why This Job is Important

This role is crucial for ensuring the functionality and performance of our data ecosystem. By analyzing user acquisition and retention data, you will help identify and resolve weaknesses and bugs in existing models, ultimately contributing to the improvement of our technologies.

What You’ll Be Doing

Monitoring and Maintenance: Lead all aspects of alerts to ensure the ecosystem’s functionality, working with existing models for day-to-day operations and performance.
Data Analysis: Analyze user acquisition and retention data, identifying weaknesses and bugs in existing models for resolution.
Analytics and Machine Learning: Run analytics to extract statistics, patterns, and design machine learning models to improve existing technologies.
Collaboration: Work closely with the development team, contributing to data/statistics tasks for improving user engagement. Collaborate with various stakeholders to formulate pertinent questions and provide actionable insights.
Data Transformation: Employ ETL tools like DBT to transform data, making it more accessible to the broader business. Use time series graphing services such as Grafana to create visualizations, monitor trends, and identify patterns.

The Ideal Skills & Experience

Experience with data-related technologies, including database queries, programming, data mining/wrangling, analysis, and reporting.
Strong proficiency in SQL, with the ability to read, write, and query effectively.
A keen curiosity about data, statistics, machine learning, and data science.
Strong problem-solving skills with an emphasis on product development, logical thinking, and critical analysis.
Experience with statistical computer languages such as Python, Scala, R, MATLAB.
Knowledge of statistical techniques and concepts, including regression, properties of distributions, statistical tests, and proper usage.
Experience using web services and languages, including AWS, EC2, S3, Redshift, DigitalOcean, etc.
Meticulous, with a good work ethic and the ability to collaborate across different teams.
Experience in Excel and Power BI is a plus.

Apply Now for Kantar Data Analyst Jobs

How to Apply Kantar Off Campus Drive 2025

Click on Apply to Official Link Kantar Above – You will go to the Company Official site
First of all Check, Experience Needed, Description and Skills Required Carefully.
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Interview Questions

  • Explain your experience with Python and SQL in previous projects.
  • How do you approach analyzing user acquisition and retention data?
  • Describe your experience in building or maintaining machine learning models.
  • How have you used ETL tools like DBT in transforming data?
  • What statistical techniques do you frequently use in your data analysis workflow?
  • Explain how you debug and improve existing models in production.
  • How do you use visualization tools like Grafana to monitor trends?
  • Describe a time you worked closely with stakeholders to generate actionable insights.
  • What challenges have you faced while working with large datasets, and how did you handle them?
  • How do you stay updated with the latest trends in data science and analytics?


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