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Title: Senior Data Analyst Batch AI

Summary of Role

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.

How You’ll Succeed

-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 Success Looks Like (First 6 Months)
-You consistently identify meaningful patterns or anomalies across plants that were not previously visible.
-Your insights contribute to discussions around Batch AI model behavior and product improvements.
-You develop a strong understanding of batching operations and how they appear in data.
-You become a trusted voice in data reviews by bringing forward thoughtful, self-driven observations—not just answering assigned questions.

What You Bring

-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.
What Sets You Apart
-You naturally dig deeper when something doesn’t look right in the data.
-You enjoy working with messy, real-world datasets and figuring things out.
-You take initiative—you don’t wait to be told exactly what to analyze.
-You have a strong sense of ownership over your work and care about the outcome.
-You are motivated by learning and improving systems, not just completing tasks.
Nice to Have
-Exposure to time-series, operational, or IoT data
-Background in manufacturing, industrial processes, or engineering
-Familiarity with SQL or BI/reporting tools
This Role May Not Be a Fit If You
-Prefer clearly defined tasks and structured problem statements
-Primarily focus on building dashboards or reports from predefined requirements
-Wait for direction rather than proactively exploring data
-Are uncomfortable working with ambiguity or incomplete information 

Who You Are

Manages Complexity: You make sense of complex, high quantity, and sometimes contradictory information to effectively solve problems.

Nimble Learning: You actively learn through experimentation when tackling new problems, using both successes and failures as learning fodder.

Tech Savvy: You anticipate and adopt innovations in business-building digital and technology applications.

Decision Quality: You make good and timely decisions that keep the organization moving forward.

Drives Results: You consistently achieve results, even under tough circumstances.

All Company Core Competencies

Customer Focus: You build strong customer relationships and deliver customer-centric solutions.

Cultivates Innovation: You create new and better ways for the organization to be successful.

Collaborates: You build partnerships and work collaboratively with others to meet shared objectives.

Instills Trust: You gain the confidence and trust of others through honesty, integrity, and authenticity.

Self-Development: You actively seek new ways to grow and be challenged using both formal and informal development channels.