Shop101 - Data Scientist

Company profile :

Shop101 is democratizing commerce in India through its social commerce platform. We are creating entrepreneurs with zero investment (with a large majority being women) and getting the next 400M users (from smaller towns) to transact online.

Shop101 is the easiest way to sell on Instagram, Facebook & WhatsApp. People can resell from a wide range of products on Shop101 Supply or sell their own products. We provide a mobile-first end-to-end ecosystem (including the supply of goods, logistics, online payments, cash-on-delivery services) around social commerce to seamlessly sell online. Entrepreneurs can create an online store for free using a smartphone in a few seconds and get complete control over inventory, customers and orders.

We are a young team of 300+ highly motivated individuals from pedigree institutions such as IITs and IIMs. At Shop101, our fundamental belief is that technology is going to be the game changer in the coming years. We are a team of geeks who take pride in solving problems by a creative use of technology. Shop101 is Series B funded by top global funds including Kalaari Capital, Unilever Ventures, Stellaris Venture Partners and Vy Capital.

A detailed profile is available at www.shop101.com/profile

Responsibilities :

- Core Personalisation algorithms - These are used for driving re-seller engagement, offers, growth/retention strategies & product suggestions, app feed prioritisation - From understanding how to gather the data for cold-start recommendations, to collaborative filtering models, to the incorporation of feedback so that the re-sellers are able to drive more business from the platform.

- Develop models that help understand and describe reseller's demog, selling cycle, acquisition pattern, reduce return, increasing the network's engagement & profit margin.

- Operations research- every day we make many small (and large) decisions, from what products to procure, which resellers to target, where to enable or disable deliveries, reduce the return rate and improving overall efficiency. Each of these decisions has a cost and benefit, along with competing trade-offs to consider

- Insights, Forecasting and predictive models- to make smart decisions, we need to have a crystal ball that tells us with a degree of certainty what will happen in the future by leveraging from tons of data harnessed till now

Skill Set :

- B Tech, MS in a quantitative discipline (e.g. math, computer science, stats, physics, engineering, operations research)

- At least 2-year experience in data science in a similar industry/ Startups

- Strong SQL skills, Good hold of NoSQL databases

- High level of proficiency in R, Python, Scala or similar modelling/scripting language

- Strong hands-on knowledge in statistics, optimization and experience developing and deploying machine learning & data visualization

- Experience developing and deploying machine learning algorithms that drive consumer engagement, forecasting, ranking & sorting, demand & logistics.

- Prior experience in e-commerce and scale-up environment preferred