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Customer Analytics Specialist

Job in 400001, Mumbai, Maharashtra, India
Listing for: EXL
Full Time position
Listed on 2026-09-27
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems & Technology Analysis, Data Scientist
Job Description & How to Apply Below
Role

Title:

Customer Analytics Specialist

At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations.

Role Overview :
We are seeking a highly skilled analytics professional who can independently design and execute end-to-end analytical solutions. This is a high-impact, high-visibility role requiring strong expertise in advanced analytics, data science methodologies, and stakeholder management.

Key Responsibilities:

1. Own and deliver

end-to-end analytical solutions

from problem definition to execution
2. Design and implement advanced analytical models to solve complex business problems
3. Apply

data science and statistical techniques

to generate actionable insights
4. Work closely with business stakeholders to shape problem statements and solution approaches
5. Translate insights into strategic recommendations and measurable business impact
6. Mentor junior analysts and guide best practices in analytics delivery
7. Drive innovation by leveraging new tools, techniques, and methodologies

Required

Skills & Experience:

1. Strong expertise in

SQL and data manipulation
2. Advanced proficiency in

Python (or equivalent)

for data analysis and modeling
3. Solid understanding of

statistics and data science methodologies
4. Proven experience in

customer analytics / behavioral analytics
5. Ability to independently manage and deliver complex projects
6. Strong

stakeholder communication and influencing skills
7. Structured thinking with a solution-oriented mindset

Preferred Qualifications:

1. Experience in retail, CRM, or customer lifecycle analytics
2. Exposure to machine learning techniques and experimentation frameworks
3. Experience working in high-paced, client-facing environments
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