Data Scientist – Applied ML & Predictive Modeling

About the job

We are looking for a hands-on Data Scientist with strong experience in regression, predictive modeling, and applied ML systems . You will own ML models end-to-end—from data understanding and feature engineering to deployment and monitoring—while also contributing to lightweight GenAI use-cases such as RAG-based tools or internal assistants. Key Responsibilities • Build and deploy regression and predictive ML models for real business problems • Perform EDA, feature engineering, and data validation on large datasets • Develop and maintain models using XGBoost, regression, and classical ML techniques • Own the full ML lifecycle : development, validation, monitoring, and improvement • Collaborate with engineers to integrate models into production systems • Experiment with Generative AI (LLMs, RAG, LangChain) for internal tools or product enhancements • Clearly document models, assumptions, and business impact What We’re Looking For • 4+ years experience in Applied ML / Data Science • Strong Python, SQL , and ML fundamentals • Proven experience with regression, classification, and tree-based models • Exposure to model deployment and production ML • Working knowledge of cloud platforms (AWS / GCP / Azure) • Practical exposure to GenAI or LangChain (not mandatory-heavy) • Strong analytical and business problem-solving skills Why Join • Real ownership of production ML models • Balanced focus on classical ML + modern AI • Product-driven, impact-oriented work • High autonomy and strong learning culture.

Requirements

• Applied ML
• Predictive Modeling
• Python
• SQL
• XGBoost

Preferred Technologies

• Applied ML
• Predictive Modeling
• Python
• SQL
• XGBoost

Benefits

• High autonomy
• Strong learning culture

About the company

We are a product-based B2B SaaS company building cloud-native platforms that help enterprises modernize and optimize their cloud and data ecosystems.