Full Stack Data Scientist

About the job

Job Description: About the Role : We are looking for a hands-on Full Stack Data Scientist who can independently manage the entire machine learning lifecycle—from data wrangling to deployment—without relying on a dedicated data engineering team. This role is ideal for someone who thrives in a fast-paced, self-directed environment and is passionate about building real-world ML solutions that drive business outcomes. Key Responsibilities : ∙Own the full ML pipeline: data ingestion, cleaning, feature engineering, model development, deployment, and monitoring. ∙Build and fine-tune models using Python and frameworks like Scikit-learn, XGBoost, TensorFlow, or PyTorch. ∙Deploy models using Databricks, MLflow, and cloud-native tools (preferably Azure). ∙Develop robust, scalable pipelines using PySpark or native Databricks workflows. ∙Collaborate with BI analysts and business stakeholders to translate requirements into production-ready solutions. ∙Maintain and improve existing models and pipelines with minimal supervision. Required Skills : ∙3+ years of experience in applied data science or ML engineering. ∙Strong Python programming skills, including experience with data manipulation and ML libraries. ∙Experience with Databricks and cloud-based ML deployment (Azure preferred). ∙Ability to work independently across the full stack of ML development and deployment. ∙Familiarity with version control (Git), CI/CD, and MLOps best practices. ∙Excellent communication skills and ability to work with remote teams across time zones. Nice to Have ∙Experience with data pipeline development using PySpark or Delta Lake. ∙Exposure to Docker, REST APIs, or real-time inference. ∙Prior experience working in a manufacturing or industrial analytics environment. Interview Process: Shortlisted candidates will be required to complete: ∙An online technical skills assessment focused on Python and applied machine learning. ∙An in-person practical test at our Ahmedabad Tech Center to evaluate real-world problem-solving and deployment capabilities. Hours: 2:30 PM – 11:30 PM IST (working from Office) Reports to: Manager, Data Analytics California, USA

Requirements

• Python
• ML libraries
• Databricks
• Cloud deployment
• Data pipeline development
• MLOps

Preferred Technologies

• Python
• ML libraries
• Databricks
• Cloud deployment
• Data pipeline development
• MLOps