Data Analyst - Python

Kantar

4 - 9 years

9 - 19 Lacs

bengaluru

Posted:None| Platform:

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Skills Required

python data analytics sql queries pandas eda modeling numpy scikit-learn sql

Work Mode

Hybrid

Job Type

Full Time

Job Description

Data Analyst

Design and develop analytical solutions for a wide range of business problems.
Combine business understanding with statistical techniques to generate actionable insights.
Perform data mining and analysis to uncover consumer behavioural patterns.
Ensure all deliverables meet client expectations in terms of scope, speed, and quality.
Understand the client domain, products (e.g. Kantar Cross-Media, Brand, Creative), and business objectives.
Manage end-to-end project lifecycle from inception to completion with minimal guidance.
Handle single and multi-country/multi-category studies (5–10 cells).
Identify and gather internal and external information required for project setup.
Source and evaluate quotes from external suppliers, ensuring cost and timing efficiency.
Recommend methodologies for non-standard projects using fieldwork expertise.
Create and manage project plans and timelines, ensuring stakeholder alignment.
Coordinate with Kantar Profiles and production teams for seamless execution.
Maintain quality control across all project stages, including script checking and deliverables.
Independently manage client communication and nurture stakeholder relationships.
Lead kick-off meetings, status calls, and review sessions.
Monitor project scope, timeline, and budget; escalate risks proactively.
Manage financial documentation and invoicing for vendors.
Log and document feedback accurately and on time.
Identify opportunities for process improvement and contribute to continuous enhancement.
Comply with ISO guidelines and internal work practices (e.g. time sheets, responsiveness).
Complete internal skill certifications (SUP Advance level topics) within defined timelines.

Strong command of Python or
SQL
for data analysis and manipulation.
Hands-on experience with
Power BI
or
Tableau
for data visualisation.
Practical application of
Data Science concepts
to solve business needs.
Experience using
Python
and
R
for statistical modelling and data analysis (preferred).
Ability to handle
diverse datasets
(structured and unstructured).
Familiarity with
Big Data frameworks
like Hadoop or Spark (beneficial).
Proficiency in
Microsoft Excel
and
PowerPoint
.
Strong analytical thinking and problem-solving skills.
Ability to manage multiple tasks and priorities under tight deadlines.

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