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Data Analyst

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Aquent
Full Time position
Listed on 2026-08-30
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineering, Data Scientist
Salary/Wage Range or Industry Benchmark: 140000 - 190000 USD Yearly USD 140000.00 190000.00 YEAR
Job Description & How to Apply Below

Aquent is partnering with a leading global innovator at the forefront of transforming manufacturing operations. This is an unparalleled opportunity to join a dynamic team dedicated to building cutting-edge AI applications from the ground up. As a pivotal contributor, you will leverage your expertise to revolutionize how manufacturing data is used, directly impacting production lines, product quality, and operational efficiency across numerous facilities.

Your work will not only solve complex challenges but also shape the future of intelligent manufacturing, offering a unique chance to see your ideas come to life and drive significant change.

About the Opportunity

Step into a truly impactful role where you will be instrumental in developing a brand-new application/system. This is a greenfield project, offering you the creative freedom to design and implement innovative AI solutions. You will have access to a wealth of manufacturing and quality data, enabling you to build sophisticated data models and AI applications that enhance safety, quality, throughput, cost-efficiency, and equipment reliability.

This role is for a true Data Scientist who thrives on digging into complex data, uncovering insights, and building solutions that have a tangible, enterprise-wide impact.

What You’ll Do
  • Translate complex operational and business challenges into measurable analytical questions and actionable use cases.
  • Identify, access, and critically assess data from diverse manufacturing sources, including operational execution systems, quality systems, equipment historians, and maintenance platforms.
  • Design and build robust analytical datasets and scalable data pipelines using industry-leading tools such as SQL, Python, Spark, and Databricks.
  • Conduct in-depth exploratory analysis, statistical studies, root-cause investigations, forecasting, optimization, and experimentation to drive data-driven decisions.
  • Develop, rigorously validate, document, and continuously monitor predictive or prescriptive models for critical use cases like downtime prediction, scrap reduction, defect detection, bottleneck identification, anomaly detection, yield optimization, and preventive maintenance.
  • Evaluate data quality, lineage, coverage, potential missingness, bias, and overall operational readiness before model deployment.
  • Transform complex analytical findings into clear, practical recommendations that empower plant personnel and leaders in their daily decision-making.
  • Create intuitive dashboards, compelling visualizations, comprehensive reports, and user interfaces that effectively communicate trends, risks, and opportunities.
  • Collaborate with data engineering, application development, and operational technology teams to successfully product ionize analytics and models.
  • Monitor model performance, detect data drift, ensure pipeline health, and track business impact post-deployment.
  • Support strategic modernization initiatives, including cloud migration, data-product development, automation, and the retirement of legacy systems.
  • Adhere to strict data governance, cybersecurity, AI governance, safety, privacy, and change-management requirements.
  • Present complex technical results to both technical and non-technical audiences, maintaining clear and thorough documentation.
  • Champion reusable analytic methods, standards, and best practices across various manufacturing domains.
What You’ll Bring Must-Have Qualifications
  • A Bachelor's degree in a technical field such as Computer Science, Computer Engineering, or a related discipline.
  • At least 8-10 years of professional experience, with a significant focus on data.
  • Extensive experience (8-10 years) in data modeling, designing and implementing effective data structures.
  • Proven expertise (8-10 years) in building and managing robust data pipelines.
  • Demonstrated ability (8-10 years) in data analytics, specifically extracting meaningful insights and building solutions from complex and often messy data.
  • Proficiency in programming languages and tools such as SQL, Python, Spark, and Databricks.
  • Strong background in applying statistics, machine learning, and optimization techniques.
  • Excellent communication skills, capable of…
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