The Role
We are looking for a Data Scientist with strong Applied ML experience, especially in regression, classification, and predictive modeling. This role focuses on solving business problems using data, with exposure to modern GenAI tools as an added advantage.
What You'll Do
- Build and improve regression and classification models for business use-cases
- Perform feature engineering, EDA, and data preparation on structured data
- Evaluate, validate, and monitor models for performance and stability
- Work closely with product and engineering teams to take models into production
- Contribute to ML lifecycle best practices (documentation, monitoring, improvements)
- Explore Generative AI / LLM use-cases such as RAG or internal AI tools (secondary focus)
What We're Looking For
- 4+ years of experience in Applied Data Science / Machine Learning
- Strong foundation in regression, classification, and predictive analytics
- Hands-on experience with Python, SQL, Pandas, NumPy
- Experience with tree-based models (XGBoost, RF, GBM)
- Exposure to ML deployment and cloud platforms (AWS/GCP/Azure)
- Working knowledge of GenAI tools (LLMs, LangChain, RAG) is a plus
Why Join Labra
- A B2B SaaS product startup building a cloud commerce & automation platform used by enterprises and ISVs to scale on AWS/Azure/GCP.
- Work on real business ML problems, not research-only work
- Clear ownership of models from development to production
- Opportunity to gradually expand into GenAI
- Product-focused, high-impact environment
- Strong focus on applied ML, real product ownership, and cloud-native systems.
