Data Scientist

Skill; Austin (TX); On-site; USD 185,976,000 - 199,752,000; Full time

Benefits offered by this job

Health benefits

Vision & dental

Retirement match

Paid time off

Training & learning

Job summary

Aquent Talent is partnering with a global leader to build a brand-new AI-driven application for manufacturing operations. This greenfield project offers creative freedom to design data models and analytics that improve safety, quality, throughput, and equipment reliability.

You will translate complex problems into measurable questions, access diverse data sources, and productionize models with dashboards and interfaces that drive decisions across facilities.

Qualifications

• Bachelor's degree in a technical field (Computer Science, Computer Engineering, or related)
• 8–10 years of professional data-focused experience
• 8–10 years in data modeling and data structures
• 8–10 years building and managing robust data pipelines
• 8–10 years of data analytics extracting insights from complex data
• Proficiency in SQL, Python, Spark and Databricks
• Strong statistics, ML and optimization background
• Excellent communication and cross-team collaboration
• US work authorization without employer sponsorship

Responsibilities

• Translate complex operational challenges into measurable analytical questions and use cases
• Access and assess data from diverse manufacturing sources
• Design and build robust analytical datasets and scalable pipelines with SQL, Python, Spark, Databricks
• Conduct exploratory analysis, forecasting, optimization, and experimentation for data-driven decisions
• Develop, validate, document, and monitor predictive/prescriptive models for downtime, scrap, defects, bottlenecks, anomalies
• Evaluate data quality, lineage and readiness before deployment
• Translate analytical findings into practical recommendations for plant personnel
• Create dashboards and visualizations communicating trends, risks, opportunities
• Collaborate with data engineering and OT teams to productionize analytics
• Monitor model performance and data drift post-deployment
• Support cloud migration and data-product modernization initiatives
• Uphold data governance, cybersecurity and AI governance standards
• Present technical results to diverse audiences with clear documentation
• Promote reusable analytical methods and best practices across domains

Skills

SQL

Python

Spark

Databricks

Data modeling

Data pipelines

Statistics

Machine learning

Communication

Cross-functional collaboration

Education

Bachelor's degree in a technical field (Computer Science / Computer Engineering)

Tools

Databricks

Job description

Overview

Placement Type: Temporary

Salary: $65-70 Hourly

Start Date: Sep 7, 2026

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. Your contributions will be pivotal in revolutionizing how manufacturing data is utilized, 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. If you thrive on digging into complex data, uncovering insights, and building solutions that have a tangible, enterprise-wide impact, this opportunity is for you.

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 productionize 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 analytical 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 presenting technical information to diverse audiences and fostering collaboration across teams.
• Legal eligibility to work in the United States without employer sponsorship (direct company sponsorship, employer as immigration employer of record, or any work authorization requiring written immigration support from an employer).

Nice-to-Have Qualifications

• Experience with application AI platform skill sets.

About Aquent Talent

Aquent Talent connects the best talent in marketing, creative, and design with the world's biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. We also offer free online training through Aquent Gymnasium. More information on our awesome benefits!

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We're about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.