Senior Data Analyst Batch AI

Command Alkon • Dallas, TX

1d

About The Position

The Senior Data Analyst will act as an investigator of real-world plant
performance, analyzing data from hundreds of concrete plants running Command
Alkon’s Batch AI to uncover inefficiencies, anomalies, and opportunities for
improvement. This role goes beyond assigned analysis. Success comes from
proactively identifying patterns others miss, asking the right questions, and
continuously exploring data to better understand how Batch AI performs in live
production environments. Working closely with a senior data scientist, this
individual will help translate data findings into insights that influence
product improvements and AI model performance.

Requirements

• 5 years of experience in data analysis, engineering, or a related field.
• Bachelor’s degree in Data Science, Engineering, Analytics, or similar (or equivalent hands-on experience).
• Strong Python skills for data analysis, investigation, and automation.
• Experience working with libraries such as pandas, matplotlib, or similar tools for exploring and understanding data.
• Comfort using modern AI-assisted development tools such as Cursor to accelerate analysis, scripting, and problem-solving.
• Experience working with real-world datasets through academic work, projects, internships, or professional roles.
• Familiarity with SQL is helpful, but not required to be highly advanced.
• Strong problem-solving ability with a desire to understand why things happen—not just report what happened.
• Demonstrated ability to independently explore data and uncover non-obvious insights (through projects, coursework, or prior work).
• Clear communication skills with the ability to explain findings simply.

Nice To Haves

• Exposure to time-series, operational, or IoT data
• Background in manufacturing, industrial processes, or engineering
• Familiarity with SQL or BI/reporting tools

Responsibilities

• Proactively explore plant performance data to identify anomalies, inconsistencies, and emerging patterns—without waiting for direction.
• Investigate root causes of batching inefficiencies such as material over-tolerance, device behavior, and system variability.
• Develop hypotheses from observed data patterns and validate them through deeper analysis.
• Partner with the senior data scientist to refine findings and connect insights to product and model improvements.
• Analyze batching data and device-level feed cycle logs to evaluate real-world system performance.
• Build and maintain Python-based analysis tools, scripts, and visualizations that help surface meaningful trends.
• Use modern development tools, including AI-assisted coding environments such as Cursor, to accelerate investigation and analysis.
• Continuously ask “why” when reviewing system behavior and challenge assumptions in the data.
• Communicate findings clearly to both technical and non-technical stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 251-500 employees