Business Analyst

Scapia; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Scapia is seeking a Business Analyst to own analytics across Commerce and Customer Support & Experience. You will partner with the Commerce and Store product teams to turn data into decisions that drive GMV, conversions, and customer satisfaction.

Responsibilities include building data models, dashboards, and forecasting tools for category growth, product performance, and inventory health while also supporting CX analytics such as ticket forecasting and sentiment analysis.

Qualifications

• Bachelor’s degree in Engineering, CS, Math, Stats, Economics, or related quantitative field.
• 1–3 years in BA/Data Analyst/Analytics at a product-based B2C org; e-commerce exposure a plus.
• Experience turning data into decisions across commerce and CX analytics.

Responsibilities

• Own analytics for Scapia's Commerce charter and CX use cases.
• Build data models and dashboards for category growth, product performance, and inventory forecasting.
• Collaborate with product, commerce, and CX teams to turn data into business decisions.
• Plan, execute, and deliver analytics projects with high quality.

Skills

SQL

Python

AI tools

BI tools

Statistics

Communication

Experimentation

Cloud

Education

Bachelor’s degree in Engineering/CS/Math/Stats/Economics or related field

Tools

Tableau

Power BI

Looker

Excel

Databricks

Airflow

AWS

GCP

Claude Code

Codex

Copilot

Job description

Scapia is a co-branded credit card built to make travel happen for people, by converting their everyday expenses into travel experiences. We’re a bunch of passionate people who work together, brainstorm, and debate with each other, and don’t stop until we’re proud of our work. Customer delight tops everything else — we’ve worked hard to create an environment of honesty and passion that sets everyone up for success.

Role :

Business Analyst, Commerce and Customer Support & Experience - owning analytics for Scapia's Commerce charter as well as org-level Customer Support & Experience use cases. You will work closely with Commerce/Store product and category teams, and with the Scapia customer support team, to turn data into decisions across both charters.

Scope of Role :

You will own the data models and analysis that power decision-making across Scapia's Commerce vertical, focused on three charter areas:

• Commerce category growth analytics - track and diagnose GMV/order growth by category, and identify the levers (new users, repeat purchase, basket size, category mix) driving or dragging growth.
• Product performance analysis - build recurring views of how products/listings perform (conversion, returns, margin, ratings) to inform catalog, pricing, and vendor decisions.
• Commerce inventory forecasting - build demand and stock-cover models that help the category/procurement teams avoid stockouts and overstock.

In addition, you will own analytics for Scapia's org-level Customer Support & Experience use cases (not limited to Commerce):

• Customer support & experience analytics — build models and dashboards that help the CX support team prioritize tickets, predict escalations, track sentiment, and plan resourcing.

Beyond these charter areas, you will:

• Work closely with business and product teams to understand challenges, break problems into analytical components, and deliver insights that influence strategy.
• Independently plan, execute, and deliver analytical projects with high quality, finding solutions to mitigate risks and dependencies along the way.
• Use AI-powered tools (Claude Code, Copilot, etc.) throughout your workflow (for SQL, Python, and reporting) to be more productive.

Example Projects You’ll Drive

Commerce Category Growth Analytics

• Category growth diagnostics: decompose GMV/order growth for each commerce category into new-user acquisition, repeat purchase, basket size, and category mix shifts — and flag which categories are decelerating and why.
• Category expansion / cross-sell: identify which category a customer is most likely to try next, based on current purchase pattern and Scapia Coins engagement, to prioritize placement, offers, and homepage real estate.

Product Performance Analysis

• Product performance scorecards: build a repeatable view of top- and bottom-performing SKUs/listings by conversion, return rate, and margin to inform catalog curation and vendor conversations.
• New product / category launch tracking: define success metrics and track performance of newly onboarded products or categories over their first 30/60/90 days, flagging underperformers early.

Commerce Inventory Forecasting

• Demand forecasting: build category/SKU-level demand forecasts using historical sales, seasonality, and the promotional calendar to reduce stockouts and overstock.
• Inventory health monitoring: build a live view of stock cover, aging inventory, and reorder triggers to support procurement and vendor discussions.

Scapia Customer Support & Experience

• Support ticket prioritization model: score and rank incoming tickets by urgency/impact so agents work the highest-priority issues first.
• Ticket escalation predictive scoring: predict which open tickets are likely to escalates, using early signals from ticket content, customer history, and agent handling, so they can be pre-empted.
• NPS sentiment analytics and recommendations: analyze NPS verbatims and support interactions to surface sentiment drivers and recommend actions to the CX org.
• Ticket/contact volume projections: forecast ticket and contact volumes by channel/category to support CX Agent staffing and resource planning.

What We're Looking For :

Education & Professional Background

• Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics, Economics, or a related quantitative field.
• 1–3 years of experience in a Business Analyst, Data Analyst, Data Scientist, or Analytics role at a product-based B2C organization; exposure to e-commerce/commerce analytics is a strong plus.

Core Skills

• Strong proficiency in SQL and Excel — able to write queries to extract, filter, and analyze data from structured and unstructured tables.
• Working knowledge of Python for data mining, analysis, statistical modeling, and machine learning.
• Working knowledge of AI-powered agents (Claude Code, Codex, Copilot, etc.) to accelerate SQL, Python, and analytical workflows.
• Hands-on experience with a BI tool (Tableau, Power BI, QuickSight, Looker, or similar).
• Solid understanding of statistical concepts (correlation, regression, segmentation, hypothesis testing, and statistical significance).
• Ability to break down complex business problems into analytical components and work collaboratively to solve them.
• Prior exposure to A/B testing or experimentation frameworks is a plus.
• Familiarity with data tools (Databricks, Airflow) or cloud environments (AWS/GCP) is a plus.

Communication Skills

• Exceptional written and verbal communication - able to explain complex findings clearly to technical and non-technical stakeholders.
• Ability to multitask and manage diverse analytical requirements simultaneously.
• Collaborative mindset with strong problem-solving skills and attention to detail.