Data Scientist - Machine Learning

Role Overview

The Data Scientist designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making. The role builds production-grade applications and workflows using Python, SQL, large language models, Retrieval-Augmented Generation, and agentic AI frameworks. It applies advanced analysis, prompt engineering, evaluation, and observability practices to deliver reliable and useful AI capabilities.

Responsibilities

• Design, develop, and implement scalable AI and Generative AI solutions.
• Build production-grade applications and workflows.
• Apply advanced analysis, prompt engineering, evaluation, and observability practices.
• Partner with cross-functional teams to translate ambiguous business needs into practical solutions.
• Communicate findings and recommendations clearly.

Requirements

• Master’s or Ph.D. degree in Data Science, Statistics, Engineering, Computer Science, Operations Research, or a related STEM field.
• 4–7+ years of industry experience in AI engineering, data science, machine learning, or applied advanced analytics.
• Advanced proficiency in Python and SQL.
• Experience with software engineering best practices including object-oriented programming, Git, and CI/CD.
• Experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata.
• Deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vector databases, and Agentic AI frameworks.
• Hands-on MLOps or LLMOps experience covering model monitoring, latency management, drift mitigation, and system reliability.
• Fluent in written and spoken English.

Skills

• Python
• SQL
• Generative AI
• MLOps
• RAG