GeoIQ

Position Overview:

We are building a new retail merchandising platform on top of that data. It answers what to stock, how much, and in which store, combining sales, catalogue, and customer data with GeoIQ’s location attributes at retail scale: thousands of stores, tens of thousands of SKUs, decisions made weekly.

As the product manager on this platform, you will own how those decisions reach the people who make them: category managers, planners and store operations teams. The models are being built alongside the product, so you will decide what gets built, in what order, and how its output fits into a buyer’s weekly planning cycle. You will work every day with data science and engineering, and what you ship changes what a store actually orders.

Responsibilities:

• Own one or more platform modules (demand forecasting, assortment planning, replenishment, new-launch allocation) from problem definition through to adoption.
• Spend time with merchandisers, category managers and store teams to understand how buying and replenishment decisions are made today, often in spreadsheets, and where that process breaks.
• Write specs that data science and engineering can build from: the decision being supported, its inputs, the business rules and constraints (minimum display quantities, pack sizes, warehouse reserves, brand rules), and what a good output looks like.
• Design the workflows that let planners act on model output with confidence: recommendation screens, overrides, explanations and exception queues.
• Define success metrics with the business (sell-through, stockouts, inventory turns, forecast accuracy, recommendation acceptance) and set up pilot-versus-control rollouts to measure them.
• Run pilots with store clusters and categories, gather feedback, and decide what changes before a module scales to the full network.
• Lead discovery when the platform extends to new brands and markets, each with its own data, supply chain and planning process.
• Keep the roadmap, priorities and trade-offs clear to merchandising, category, supply chain and leadership teams.

Expectations:

• Work experience: 2–5 years, with at least 2 years in product management
• Prior experience taking a product from problem definition to adoption by real users
• Comfortable with data: able to write SQL, work through a spreadsheet model, and read a model evaluation or A/B test result
• Clear written communication, including specs that engineers and data scientists can build from without a meeting
• Understanding of how ML-driven products differ: probabilistic outputs, accuracy limits, and the need for user overrides
• Experience with B2B, internal tools or data-heavy products will be an added advantage
• Experience in retail, e-commerce, merchandising, supply chain or inventory planning will be an added advantage
• Prior experience as an analyst, engineer or data scientist will be an added advantage

Join us early and own the product that decides what thousands of stores stock each week, working directly with the merchants who use it and the team that builds it.

About GeoIQ: 

GeoIQ(a Lenskart subsidiary) is a location intelligence platform that provides comprehensive data and insights to help businesses make informed decisions about their retail operations and expansion. It offers a range of data points, including demographic information, commercial activity, and market performance indicators, to give users a detailed understanding of a specific location or market. 

About the team: 

Our agile team, consisting of 40+ members, is led by a founding team with extensive experience in data analytics, machine learning, and product development. Embrace the opportunity to collaborate with seasoned professionals in a dynamic and innovative work environment. 

Responsibilities: 

• We’re looking for a Backend Engineer who thrives on solving real-world problems and is eager to build scalable, high-performance systems. You should have:
• Keen interest and ability to learn and continuously adapt to the market and technology.
• At least 2–4 years of relevant backend development experience.
• Strong knowledge and experience in Python (Flask) and SQL (we use PostgreSQL and PostGIS).
• Hands-on experience with MongoDB, Airflow and Nginx.
• Practical experience with Cloud Services, including:
• Familiarity with Google Cloud Platform (GCP): Cloud Functions, Cloudbuild, Cloud Storage, Cloud SQL, Cloud Logging, and Cloud Monitoring.
• Familiarity with Kubernetes is a bonus.
• Familiarity with GIS concepts is a plus.
• Strong background in designing and building REST APIs, with the ability to discuss architectural trade-offs and make sound technical decisions.

Why Explore a Career at GeoIQ: 

• Be part of a team that is revolutionizing decision-making for businesses across India.
• Work in a dynamic and innovative environment with ample opportunities for professional growth and learning.
• Contribute to the growth and success of a leading hyperlocal location AI startup in India. 

If you are passionate about creating intuitive and efficient front-end solutions and meet the requirements listed above, we would love to hear from you. Apply now to join our team at GeoIQ!

About GeoIQ: 

GeoIQ(a Lenskart subsidiary) is a location intelligence platform that provides comprehensive data and insights to help businesses make informed decisions about their retail operations and expansion. It offers a range of data points, including demographic information, commercial activity, and market performance indicators, to give users a detailed understanding of a specific location or market. 

About the team: 

Our agile team, consisting of 40+ members, is led by a founding team with extensive experience in data analytics, machine learning, and product development. Embrace the opportunity to collaborate with seasoned professionals in a dynamic and innovative work environment. 

Responsibilities: 

• Develop and maintain GeoIQ's products primarily using React, Redux, and NextJS.
• Ship simple, approachable, performant, and testable code. 
• Enhance user experience by creating intuitive UIs that enable data visualization and discovery.  Dive into legacy code to understand and improve current products. 
• Facilitate and make informed technical decisions that drive the long-term vision for GeoIQ. 
• Build workflow tools that allow users to explore GeoIQ's data repository, visualize spatial data, and create no-code AI models. 
• Solve complex architecture problems in an extensible and maintainable way. 
• Bring clarity to complex technical problems across the organization. 
• Participate in the design process by listening to users, attending design critiques, and providing guidance and feedback informed by a deep understanding of technical constraints. 
• Collaborate with team members to achieve clean and efficient code. 

Requirements: 

● Fluent and proficient in React with a minimum of 2 years of experience. 

● Previous experience working with geo-spatial data. 

Why Explore a Career at GeoIQ: 

• Be part of a team that is revolutionizing decision-making for businesses across India. 
• Work in a dynamic and innovative environment with ample opportunities for professional growth and learning.
• Contribute to the growth and success of a leading hyperlocal location AI startup in India. 

If you are passionate about creating intuitive and efficient front-end solutions and meet the requirements listed above, we would love to hear from you. Apply now to join our team at GeoIQ!

Position Overview:

We are building a new retail merchandising platform on top of that data. It answers what to stock, how much,

and in which store—combining sales, catalogue, and customer data with GeoIQ’s location attributes at retail

scale: thousands of stores, tens of thousands of SKUs, decisions made weekly.

As part of the data science team on this platform, you will build the forecasting, assortment and

recommendation models behind those decisions. The platform is new, so the models are being built now, not

maintained. Hands-on modelling with senior review — what you ship changes what a store actually orders.

Responsibilities:

● Build SKU- and store-level demand forecasts, including for new products with little or no sales history.

● Build assortment models — which products earn shelf space in which stores or store clusters, and how

a range change is likely to play out.

● Build recommendation and ranking models for product discovery, cross-sell and bundling, including

cold-start for new products and customers.

● Engineer features from sales, seasonality, promotions, pricing, catalogue hierarchy, store attributes and

GeoIQ’s location and demographic layers.

● Handle the realities of retail data: intermittent demand, stockouts censoring true demand, returns and

cannibalisation between similar SKUs.

● Design backtests and A/B tests that reflect how planners use the output; monitor deployed models for

drift.

● Build data pipelines and work with engineering to take models to production.

● Communicate findings to merchandising, category, and product teams.

Expectations:

● Proficient in Python

● Work experience: 1–3 years

● Prior experience with building ML models end-to-end

● Prior experience with SQL

● Knowledge of statistical techniques and model evaluation

● Experience with time-series forecasting or recommender systems will be an added advantage

● Experience with retail, e-commerce, supply chain, or spatial data will be an added advantage

Join us early and help build the merchandising brain for retail at national scale — close to the product and the

customer, with the freedom of a platform still being shaped.