Senior Data Scientist / AI Engineer
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,
Technical Tools
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
Location & Eligibility
Where is the job
Columbus, United States
On-site at the office
Who can apply
US
Listing Details
- First seen
- July 7, 2026
- Last seen
- July 13, 2026
Posting Health
- Days active
- 88
- Repost count
- 0
- Trust Level
- 17%
- Scored at
- October 4, 2026
Signal breakdown
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