Senior Data Scientist / AI Engineer

United States·Columbussenior

Data ScientistData

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Quick Summary

Key Responsibilities

Own end-to-end AI/ML solution delivery from problem definition to production Build and maintain data pipelines using PySpark and Spark on Azure Databricks Perform feature engineering,

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Data ScientistData

Responsibilities

~1 min read

→Own end-to-end AI/ML solution delivery from problem definition to production
→Build and maintain data pipelines using PySpark and Spark on Azure Databricks
→Perform feature engineering, data preparation, and model development
→Develop, deploy, and monitor ML models and AI agents
→Implement agentic AI workflows with multi-step reasoning and tool usage
→Track experiments and deployments using Mlflow
→Monitor model performance, drift, and reliability in production
→Collaborate with business, data engineering, and analytics teams
→Mentor junior team members and promote best practices

Strong hands-on experience in Python and SQL
Experience with PySpark, Spark, and Azure Databricks
Solid understanding of ML workflows and evaluation techniques
Experience with MLflow and MLOps fundamentals
Exposure to LLMs, AI agents, and GenAI frameworks (LangChain/Semantic Kernel preferred) Experience & Education
5–6 years of hands-on experience in Data Science, ML, or AI Engineering
Proven experience delivering ML/AI solutions in production
Experience in cloud environments, preferably Azure
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field