Full Stack Data Scientist – Data Analytics Team

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