Data Scientist - INTL - India

Insight Global
Pittsburgh, United States of America
7 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Pittsburgh, United States of America

Tech stack

Java
JavaScript
Artificial Intelligence
Computer Programming
Distributed Data Store
Python
Machine Learning
MySQL
Software Deployment
Software Engineering
Software Testing Automation Framework
Spark
Generative AI
Information Technology
Machine Learning Operations
Databricks

Job description

We are seeking a Data Scientist to lead the strategy, design, development, and production deployment of Data Science, AI, and ML solutions across Enterprise GenAI applications. This role owns initiatives from end-to-end, partnering closely with business stakeholders to drive GenAI-enables innovation across products. This individual will leverage MLOps frameworks and advanced analytics models to build scalable ML-enabled GenAI products, and should have experience developing solutions from POC to deployment.

Requirements

  • 5-7+ years of experience in Digital, Data, Software Engineering, or Statistics, including 5+ years in Applied AI/ML and Data Science

  • Proven end-to-end ownership of ML initiatives from ideation through production deployment

  • Deep hands-on knowledge of machine learning, AI techniques, and applied statistics

  • Experience with distributed data and compute platforms (e.g., Azure Databricks, Spark, MySQL)

  • Strong programming experience in Python (additional languages such as Java, R, or JavaScript preferred)

Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science, Engineering, or related field · Master's degree in Data Science, AI/ML or related discipline

  • Experience defining standards, best practices, and automation framework for ML and analytics

  • Relevant certifications in Data Science, AI, or ML

Prior experience supporting multiple products or lines of business in an enterprise environment

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