Full Stack Data Scientist – Data Analytics Team

Full Stack Data Scientist – Data Analytics Team

1 Nos.
117203
Full Time
3.0 Year(s) To 5.0 Year(s)
18.00 LPA TO 24.00 LPA
IT Software - Client Server
Industrial Products/Equipment/Machinery/Projects & Engg
B.Sc - Computers; B.Tech/B.E. - Computers; BCA/BCS - Computers; M.E./M.Tech - Computers; M.Sc / MS Science - Computers
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 DatabricksMLflow, 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 DockerREST 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 
Company Profile

Since its founding more than 60 years ago, the company  has grown into a global company and leading producer of monolithic --- ceramics. They serve multiple industries with a commitment to providing exceptional service and top quality refractories and precast shapes.

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