Business Analyst

About the Company

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 escalate, 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.