Data Engineer / Scientist

Prasanz; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Prasanz is seeking a hybrid Data Engineer / Scientist to bridge model development with database processing in Hyderabad. You will analyze system data, train predictive models, and build feature stores to support production deployments.

The role requires 4+ years of experience, strong Python including Pandas, Numpy and Scikit-learn, SQL proficiency, and experience containerizing models and deploying them to cloud environments.

Qualifications

• 4+ years of professional experience in data analysis, ML, and data pipelines.
• Strong Python with Pandas, Numpy and Scikit-learn.
• Proficient SQL for querying databases and processing logs.
• Solid foundations in probability, statistics, and linear algebra.
• Experience containerizing models and deploying to cloud environments.

Responsibilities

• Clean, aggregate, and analyze high-volume business data using Pandas and SQL.
• Build, evaluate, and tune ML models (classification, regression, clustering).
• Write optimized SQL and Python to construct feature stores.
• Deploy models as scalable inference APIs inside Docker containers.
• Formulate hypotheses, run tests, and present insights to stakeholders.

Skills

Python

Pandas

Numpy

Scikit-learn

SQL

Statistics

Jupyter

Tools

Docker

Job description

Back to Open Positions

Data & AI

Data Engineer / Scientist

Full-Time Hyderabad, India (Offshore) Posted 6/23/2026

Primary Technology Stack

PythonPandasScikit-learnSQLStatisticsJupyterDocker

About The Role

Seeking a hybrid Data Engineer / Scientist to bridge model development with database processing. You will analyze system data, train predictive models, and build feature stores to support production deployments.

Key Responsibilities

• Clean, aggregate, and analyze high-volume business data using Pandas and SQL.
• Build, evaluate, and tune machine learning models (classification, regression, clustering).
• Write optimized SQL and Python queries to construct database feature stores.
• Deploy trained models as scalable inference API endpoints inside Docker containers.
• Formulate business hypotheses, run statistical tests, and present insights to stakeholders.

Required Qualifications

• 4+ years of professional experience across data analysis, machine learning, and pipeline builds.
• Proficient in Python, including numerical and ML libraries (Pandas, Numpy, Scikit-learn).
• Strong SQL proficiency, with experience querying databases and processing transactional logs.
• Solid mathematical foundations (probability, regression, statistics, linear algebra).
• Experience containerizing models and deploying them to cloud staging environments.