Habuild is one of India’s fastest-growing wellness platforms, dedicated to helping people build healthier lives through the power of daily yoga, consistency, and community. With over 9 million lives impacted and 4.5 lakh+ people joining daily, our mission is simple yet ambitious: make wellness a lifelong habit for everyone.

Founded by a passionate team from IITs and IIMs, Habuild is a product-first, experiment-driven company obsessed with creating real user impact. We've already broken multiple world records—and we're just getting started.

We’re not just building a company—we’re building a movement. A movement fueled by purpose, discipline, and the belief that small, consistent actions lead to extraordinary transformation. Our work spans yoga, mindfulness, habit-building, and digital wellness, empowering people to unlock their best selves.

As a Data Scientist at Habuild, you will lead the design and deployment of data-driven systems that power personalized experiences and intelligent decision-making across our platform. This role demands a self-starter mindset with strong hands-on experience in data engineering, model development, and end-to-end deployment of scalable machine learning systems.

We are looking for a generalist profile—someone who has explored multiple areas within Data Science, such as recommendation engines, LLMs (Large Language Models), and audio/video models, rather than being confined to one domain. You’ll work cross-functionally to translate real-world problems into scalable AI solutions that directly impact millions of users.

Own and lead end-to-end Data Science projects—from data ingestion and preprocessing to modeling and deployment.

Design and implement scalable pipelines for data processing, normalization, and feature engineering.

Build, train, and deploy machine learning models in areas such as recommendation systems, natural language processing (LLMs), and multimedia (audio/video) analysis.

Collaborate with engineering, product, and business teams to identify impactful use cases and align model development with company goals.

Monitor model performance and continuously optimize for accuracy, efficiency, and scalability.

Document technical decisions, processes, and outcomes to ensure clarity and maintainability.

Mentor junior team members and contribute to the growth of data science best practices within the organization.

Experience: 3+ years of relevant experience in Data Science or Machine Learning, preferably in product-focused environments.

End-to-End Project Ownership: Strong background in handling projects independently, including data engineering, modeling, and deployment.

Technical Stack: Proficiency in Python, SQL, and experience with cloud platforms (AWS/GCP), model deployment frameworks (Docker, FastAPI), and ML libraries (scikit-learn, TensorFlow, PyTorch).

Domain Breadth: Experience across multiple areas such as recommendation systems, LLMs, audio/video models, and time-series analysis.

Data Engineering Skills: Hands-on experience building pipelines, working with large-scale datasets, and integrating data from diverse sources.

Problem-Solving: Strong analytical thinking with a practical, product-focused mindset.

Communication: Ability to present complex concepts clearly to both technical and non-technical stakeholders.