Category Manager

Location: Bangalore

Experience: 35 years

Education: MBA is highly desirable. Also B.Tech is degree preferred

Salary: 15-20 LPA

Role Overview

We are looking for a sharp, analytical, and business-minded Pricing & Data Analyst who can evaluate apartments using both market intuition and data science. In this role, you will assess properties based on location, size, floor, age, amenities, condition, and comparable sales to arrive at accurate price recommendations. Your analysis will directly influence acquisition decisions, pricing strategy, and business margins. This is a high-ownership role with visible impact on the companys day-to-day operations.

Key Responsibilities

Apartment Pricing & Valuation

• Evaluate apartments for acquisition by analysing location, project, configuration, floor, facing, condition, and comparable transactions.
• Arrive at a price recommendation for each property using data, market knowledge, and internal pricing models.
• Conduct on-ground and data-driven research on micro-markets, projects, and localities across Bangalore.
• Track and analyse property registrations, listings data, and broader real estate market trends.

Pricing Model Development & Improvement

• Work with Python, including pandas, numpy, and scikit-learn, to build, test, and refine pricing algorithms.
• Identify gaps, biases, and inaccuracies in the current model and recommend improvements.
• Build automated data pipelines to ingest transaction data, listings, and market signals.
• Run backtesting and validation to compare pricing model outputs with actual sale prices.

Data Analysis & Reporting

• Build dashboards and reports to track pricing accuracy, margins, and market trends.
• Analyse acquisition performance, including time to sell, realised margin, and pricing errors.
• Use SQL to query and extract insights from the transaction database.
• Present data-backed recommendations to leadership on pricing strategy and market-entry decisions.

Qualifications

Must-Have

• 35 years of experience in data analytics, pricing, business intelligence, or a quantitative role.
• Strong proficiency in Python, especially pandas, numpy, and matplotlib; scikit-learn exposure is a plus.
• Solid SQL skills, including complex queries on large datasets.
• Strong Excel or Google Sheets skills, including advanced formulas, pivot tables, and data modelling.
• Strong analytical ability to assess property pricing using both data and market context.
• Comfort working with messy, ambiguous real estate data.
• Excellent communication skills, with the ability to explain pricing rationale to non-technical stakeholders.