Senior Data Scientist

Job Description

Company Description:

We are surrounded by the world&aposs 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&aposs 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 &aposThe World&aposs Largest Internet Restaurant Company&apos in the last few years. Rebel Foods&apos current presence is 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.

Job Description

We are seeking a Principal Data Scientist / Manager to lead a high-impact team of 3 to 4 Data Scientists within the Data Science & Analytics (DSA) team. This is an individual contributor and managerial role combined, that blends with the deep technical expertise of Data Science, GenAi, ML along with people management and business acumen. Youll be at the forefront of designing and scaling ML systems that power critical decisions across Rebels fast-evolving business landscape. 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. 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, Data Science intelligence, reports automation and real-time dashboards used across the organization. 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.

What Youll Own

- Lead and mentor a team of data scientists to develop and scale high-impact ML solutions.
- Partner with cross-functional teams including Product, Engineering, Operations, Marketing, and CX to translate business problems into structured data science problems.
- Define and drive the data science roadmap, ensuring alignment with organizational strategy and quarterly OKRs.
- Oversee end-to-end ML pipelines data ingestion, modeling, validation, deployment, monitoring, retraining, and automating performance measurement.
- Advocate for ML best practices, model governance, and scalable experimentation frameworks.
- Act as the DS point-of-contact for senior leadership, presenting insights and model outcomes in a business-friendly narrative.

Ideal Background & Skills

- 3+ years of industry experience, with at least 1+ years leading teams or mentoring junior data scientists.
- Proven expertise in designing and deploying ML models for real-world use cases such as regression, classification, demand forecasting, clustering, NLP, recommender systems, or optimization.
- Hands-on experience with Python, SQL, ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), and cloud ML platforms like Amazon SageMaker.
- Strong foundations in statistics, probability, and experimentation (e.g., A/B testing, uplift modeling).
- Ability to balance technical depth with cross-functional communication simplifying ML to influence decision-making across business teams.
- Experience managing the lifecycle of ML models in production, including monitoring, retraining, and performance debugging.

Nice to Have

- Hands-on experience with Large Language Models (LLMs) and familiarity with prompt engineering.
- Experience integrating DS outputs into production-grade systems or dashboards (via APIs, dashboards, BI tools). Understanding of MLOps
- Familiarity with start-up or fast-paced environments and agile ways of working.
- A love of food (Yes, we really do have food tasting sessions at the office)

Learn more about Rebel here: [Confidential Information]

---