Data Analyst at Laundryheap

Apply for the Data Analyst position at Laundryheap in Bengaluru. Optimise international logistics, dynamic pricing, and marketplace analytics using SQL, Python, Looker Studio, and Tableau.

About the Company: Laundryheap

Laundryheap is an award-winning, industry-leading startup completely transforming the traditional laundry and dry cleaning ecosystem. Operating across more than 14 intense global markets—with hyper-growth expansions across Europe, Asia, and North America—Laundryheap delivers pristine garments back to consumers within a strict 24-hour window. This makes them one of the fastest, most reliable on-demand logistics services in the global marketplace.

The Global Analytics Division at Laundryheap serves as the central optimisation layer for this complex, fast-moving operation. Based in the technology innovation capital of Bengaluru, Karnataka, the data team is tasked with balancing on-demand courier routes, auditing volatile marketplace capacities, and parsing localised transaction histories across multiple continents. They turn multi-market datasets into direct operational breakthroughs that protect the company’s 24-hour service delivery promise.

About the Role: Data Analyst

Are you a sharp, fast-learning data specialist who wants to work directly on high-impact pricing and logistics strategy? Laundryheap is hiring a full-time, permanent Data Analyst to join its corporate analytics squad in Bengaluru, Karnataka, India. This execution-oriented role is built for proactive analysts who want total ownership of their data pipelines and direct access to cross-functional global leadership.

As a Data Analyst at Laundryheap, you will step out of passive data extraction to serve as a critical strategic advisor. Your daily work will center on building and testing automated pricing models, tracking multi-market demand forecasting, and auditing inventory systems. You will write high-performance SQL scripts, automate processing routines using Python, and engineer self-service dashboard suites. Because you will partner directly with international marketing, pricing, and operations teams, you must excel at translating mathematical trends into clear, decision-oriented business stories.

Key Responsibilities & On-Demand Marketplace Workflows

• Multi-Market Trend Dissection: Analyse massive, unorganised logistics and transaction datasets to uncover underlying demand spikes, processing patterns, and revenue opportunities.

• Dynamic Data Querying: Write highly efficient, scalable SQL queries to extract, join, and manipulate information across distributed relational databases.

• Scripting & Process Automation: Write Python routines to automate manual data cleaning steps, run advanced statistical transformations, and accelerate weekly financial reconciliations.

• BI Interface Engineering: Build and optimise interactive, clean operational dashboards within Looker Studio, Tableau, and advanced Google Sheets environments.

• Pricing & Forecast Architecture: Help develop and iterate predictive pricing models, local forecasting tools, and automated inventory tracking modules.

• Cross-Functional KPI Alignment: Partner with international operations and marketing teams to establish regional key performance indicators (KPIs) and track pilot project success.

• Executive Technical Storytelling: Present complex data models and operational risks in a simple, structured, and highly compelling way to both technical engineers and senior executives.

Candidate Prerequisites & Key Technical Skills

Successful candidates must combine a strong grasp of data structures with the mental agility to thrive in a fast-paced, fluid startup environment.

Required Experience & Technical Baseline:

• Core Querying Mastery: Advanced, mandatory proficiency in writing structured queries in SQL to mine data without supervision.

• Advanced Spreadsheet Engineering: High-level mastery of Google Sheets and Microsoft Excel, including complex logical formulas, nested lookups, index-match overrides, array structures, and manual data modelling.

• Programming Adaptability: Direct experience or clear practical familiarity using Python (or an equivalent scripting language) for data engineering and automation tasks.

• Business Intelligence Tooling: Hands-on experience building, structuring, and deploying client-facing reports within Looker Studio and Tableau.

• Problem-Solving Mindset: A natural ability to take messy, open-ended business issues, break them down into structured data problems, and maintain absolute attention to data integrity.

Preferred Qualifications (Nice-to-Have):

• Logistics & E-Commerce Exposure: Prior experience working with operational analytics inside an e-commerce, on-demand delivery, or service-based platform.

• Specialised Domains: Direct exposure to dynamic pricing calculations, marketplace economics, or automated routing data.

• Experimentation Foundations: Foundational understanding of A/B testing frameworks, multivariate experimentation, and statistical forecasting models.

Core Position Specifications

• Position Title: Data Analyst

• Hiring Organisation: Laundryheap

• Corporate Work Location: Bengaluru, Karnataka, India

• Employment Framework: Full-Time, Permanent corporate assignment

• Experience Target: Mid-Level Specialist Track

• Operation Framework: Fast-Paced Global Marketplace Architecture

• Industry Placement: Tech Startup / On-Demand Logistics / E-Commerce Retail

• Functional Department: Global Business Intelligence & Marketplace Analytics