Data Scientist – Applied ML & Predictive Modeling

About the job

The Role 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.

Requirements

• Applied ML
• Predictive Modeling
• Regression
• Python
• SQL

Preferred Technologies

• Applied ML
• Predictive Modeling
• Regression
• Python
• SQL

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. Our AI work focuses on applied machine learning, predictive analytics, and selective use of Generative AI where it delivers real business value.