Senior BI Analyst

2 weeks ago


Bengaluru, Karnataka, India Weekday AI Full time
This role is for one of Weekday's clients
Salary range: Rs 100000 - Rs 2000000 (ie INR 10-20 LPA)
Min Experience: 5 years
Location: Bengaluru
JobType: full-time

Requirements

About the Role

We are seeking a highly skilled and analytical Senior BI Analyst – Loyalty CRM (Mobility) to join our team. The role requires a strong background in churn analysis, loyalty programs, campaign measurement, Power BI, and Python, coupled with a deep understanding of retail and mobility business models. As a key member of the analytics team, you will be responsible for designing and delivering insights that enhance customer engagement, optimize campaigns, and support loyalty and retention strategies.

This role involves partnering closely with merchandising, marketing, e-commerce, and operations teams to ensure that data-driven decisions improve customer experience and business outcomes. You will leverage advanced analytical tools and methodologies to evaluate campaign effectiveness, diagnose business challenges, and recommend actionable strategies.

Key Responsibilities

- Churn & Loyalty Analysis: Conduct in-depth churn analysis to identify drivers of customer attrition, recommend retention strategies, and evaluate the effectiveness of loyalty programs.
- Retail Analytics: Analyse sales, inventory, pricing, and customer behavior data to uncover insights that drive merchandising, marketing, and operational decisions.
- Campaign Analytics:

- PCA (Post Campaign Analysis): Assess campaign outcomes, customer behavior, and performance metrics to determine effectiveness.
- RCA (Root Cause Analysis): Identify issues behind campaign failures, anomalies, or deviations from expected outcomes.
- Deep Dive Analysis: Use SQL, Excel, Power BI, and other tools to explore customer segments, trends, and KPIs.
- Performance Evaluation: Measure campaign effectiveness across open rates, CTR, conversion rates, ROI, uplift, and engagement metrics.

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- Campaign Support: Collaborate with business teams to support campaign operations, including audience selection, execution, troubleshooting, and reporting.
- Business Partnership: Partner with merchandising, e-commerce, marketing, and operations teams to enable initiatives like demand forecasting, promotion effectiveness measurement, and assortment planning.
- Experimentation: Design and execute A/B tests and other statistical analyses to validate strategies and improve campaign design.
- Dashboarding & Reporting: Build and maintain interactive dashboards in Power BI to deliver business-critical insights and self-service reporting.
- Advanced Analytics: Use Python for ETL, modeling, forecasting, and automation to improve data quality and enhance decision-making.
- Continuous Improvement: Identify opportunities to streamline processes, improve campaign measurement frameworks, and build scalable analytics solutions.

Core Competencies

- Strong expertise in churn analysis, loyalty programs, and CRM analytics.
- Proficiency in Power BI for dashboard creation and data visualization.
- Solid programming skills in Python and experience with SQL for data handling.
- Ability to conduct PCA, RCA, and deep-dive analyses to support business problem-solving.
- Experience with campaign design, measurement, and optimization across retail and mobility businesses.
- Strong understanding of sales, pricing, promotions, inventory, and customer behavior analytics.
- Excellent collaboration skills with cross-functional teams.
- Strong communication and storytelling abilities to present complex insights to non-technical stakeholders.

Qualifications

- Bachelor's/Master's degree in Business Analytics, Data Science, Statistics, Computer Science, or a related field.
- 5+ years of experience in BI, CRM analytics, loyalty program analysis, or retail analytics.
- Hands-on expertise in SQL, Power BI, and Python.
- Experience working in mobility, retail, or loyalty program environments preferred.
- Strong business acumen, problem-solving mindset, and ability to translate data into strategy.

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