Data Scientist II

Overview

About Us

We are surrounded by the world's leading consumer companies led by technology - Amazon for retail, Airbnb for hospitality, Uber for mobility, Netflix and Spotify for entertainment, etc. Food & Beverage is the only consumer sector where large players are still traditional restaurant companies. At Rebel Foods, we are challenging this status quo as we are building the world's most valuable restaurant company on the internet, superfast.

The opportunity for us is immense due to the exponential growth in the food delivery business worldwide which has helped us build 'The World's Largest Internet Restaurant Company' in the last few years. Rebel Foods' current presence in India, UAE & UK with close to 50 brands and 4500+ internet restaurants has been built on The Rebel Operating System.

While for us it is still Day 1, we know we are in the middle of a revolution towards creating never seen before customer-first experiences. We bring you a once-in-a-lifetime opportunity to disrupt the 500-year-old industry with technology at its core.

We urge you to refer to the below to understand how we are changing the restaurant industry before applying at Rebel Foods.

https://spirit.rebelfoods.com/why-is-rebel-foods-hiring-super-talented-engineers-b88586223ebe

https://spirit.rebelfoods.com/how-to-build-1000-restaurants-in-24-months-the-rebel-method-cb5b0cea4dc8

https://spirit.rebelfoods.com/winning-the-last-frontier-for-consumer-internet-5f2a659c43db

https://spirit.rebelfoods.com/a-unique-take-on-food-tech-dcef8c51ba41

Job Description

We are looking for a Data Scientist-II to join our Data Science & Analytics (DSA) Team. You will get to work with other data scientists, analysts, data engineers, PMs and business teams on some of the toughest and most interesting problems in our industry. Our work spans across areas of inventory forecasting, order predictions, marketing spend optimization, delivery time prediction, personalization, customer insighting, product recommendations, supply chain planning, capacity optimization, and more. The role will involve understanding business problems, designing relevant ML solutions, building & deploying new models, maintaining & enhancing existing models, and automating performance measurement of the same. We are looking for someone who is excited to work in a fast-growing industry, has a spirit of ownership & collaboration, and loves seeing the impact of what they have built at scale!

What our team owns

At Rebel, the Data Science & Analytics team builds and maintains all ML models, rule-based intelligence, automated reports and dashboards used by the organization. We are on a mission to drive business impact via ML and Data Science and grow adoption of these areas at Rebel. We also want to enable the organization to better understand and effectively use ML and DS. We interact with teams across every business area such as Supply, Operations, Demand Generation, D2C, Finance, Brands, Customer Delight, Central Planning and many more. We are never short of interesting challenges and we balance delivering continuous impact and great CX, while building strong foundations to drive sustainable ML returns over time.

Specific Qualifications

● Strong working knowledge of a variety of machine learning techniques (Regression, Classification,Clustering, Decision Tree, Probability Networks, Neural Networks, Bayesian models etc.)

● Proficient in Python, SQL, and machine learning libraries (e.g., TensorFlow,scikit-learn).

● Experience in working with varied data types (structured and unstructured) and databases

● Experience with Machine Learning and related technologies such as Python, Tensorflow, Amazon SageMaker

● Excellent problem-solving skills with a demonstrated ability to think analytically and strategically.

Good-to-have

● 4+ yrs experience solving NLP-based problems or working with LLMs / prompt engineering

● Working with non-tech stakeholders and explaining ML performance in simple language

● A love of food (Yes, we have regular tasting sessions at office!)