1 Opening(s)
3.0 Year(s) To 5.0 Year(s)
18.00 LPA TO 24.00 LPA
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
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