Manufacturing Data Scientist

TriMas Corporation; California (MO); Remote; USD 100,000 - 135,000; Full time

Job summary

Allfast Fastening Systems LLC seeks a Manufacturing Data Scientist to translate complex shop-floor data into actionable insights, partnering with manufacturing, quality, and supply chain teams. The role emphasizes Python/SQL expertise, ERP data handling, and predictive modeling to improve productivity and cost efficiency.

You will build data pipelines, develop models for reliability and planning, and create dashboards to clearly communicate results to both technical and nontechnical stakeholders.

Qualifications

• Bachelor's degree in data science, statistics, mathematics, computer science, engineering, operations research, or related field.
• 3+ years of professional experience in data science, analytics, ML, or related field.
• 2+ years of ERP data and operational data experience (production orders, BOMs, routings, inventory, costing).
• 2+ years of BI tools such as Power BI, Tableau, Looker.
• Ability to translate ambiguous objectives into clearly defined problems.
• Strong written, verbal, and visual communication skills.
• Fluency in Python with common libraries (pandas, NumPy, scikit-learn).
• Fluency in SQL with complex queries, joins, CTEs, window functions.
• Experience preparing, cleaning, joining, and analyzing large datasets from multiple systems.
• Experience applying statistical analysis, ML, forecasting, optimization, anomaly detection.
• Strong understanding of data validation, model evaluation, and experimental design.
• Ability to collaborate with technical and manufacturing stakeholders.

Responsibilities

• Analyze manufacturing, production, quality, maintenance, inventory, and supply-chain data to identify trends, risks, and improvement opportunities.
• Build, validate, and maintain data pipelines and reusable analytical datasets using SQL and Python.
• Develop predictive and prescriptive models for equipment reliability, maintenance, quality forecasting, yield optimization, demand planning, inventory optimization, and production scheduling.
• Extract, clean, reconcile, and integrate data from ERP, MES, quality systems, sensors, and other sources.
• Create dashboards and visualizations to communicate performance and model results clearly.
• Conduct root-cause analyses related to production losses, downtime, scrap, and process variation.
• Monitor KPIs such as OEE, first-pass yield, capacity utilization, downtime, and inventory accuracy.
• Document data sources, methodologies, assumptions, and model limitations.
• Promote data literacy and best practices across teams.
• Ensure data governance, security, quality, and regulatory compliance.

Skills

Python

SQL

ERP systems

Power BI

Tableau

Looker

Data cleaning

Data visualization

Communication

Machine learning

Education

Bachelor's degree in data science / related quantitative field

Tools

Git

dbt

LLM APIs

Job description

Manufacturing Data Scientist

Company: Allfast Fastening Systems LLC

Primary Location: 15200 Don Julian Road, City of Industry, CA 91745 USA

Workplace Type: Remote

Employment Type: Salaried | Full-Time

Function: Information Systems

Equal Opportunity Employer Minorities/Women/Veterans/Disabled

About PennAero:

PennAero is a leading manufacturer of highly engineered fasteners and specialized components for critical aerospace, defense, space, and advanced energy applications. We partner with customers to solve their most complex challenges, bringing technical depth and disciplined, agile execution when it matters most. Experience guides our growth-strengthening capabilities and expanding our global platform as markets evolve. To learn more about PennAero's capabilities and commitment to aerospace excellence, visit https://pennaero.com

Position Overview

We are seeking a Manufacturing Data Scientist to transform complex operational data into actionable insights that improve productivity, quality, cost, reliability, and supply-chain performance. This role will partner with manufacturing, engineering, quality, supply chain, finance, and information technology teams to develop analytical solutions that support data-driven decision-making across the organization. The ideal candidate has strong expertise in Python and SQL, experience working with enterprise resource planning systems, and a practical understanding of manufacturing processes and data. This individual must be comfortable working with large, complex datasets and translating analytical findings into clear recommendations for technical and nontechnical stakeholders.

Key Responsibilities

• Analyze manufacturing, production, quality, maintenance, inventory, and supply-chain data to identify trends, risks, inefficiencies, and improvement opportunities.
• Build, validate, and maintain data pipelines and reusable analytical datasets using SQL and / or Python
• Develop predictive and prescriptive models for applications such as equipment reliability, predictive maintenance, quality forecasting, yield optimization, demand planning, inventory optimization, and production scheduling.
• Extract, clean, reconcile, and integrate data from ERP systems, MES, quality systems, equipment sensors, HCM systems, and other operational sources
• Partner with manufacturing engineers, plant leaders, quality teams, supply-chain professionals, and business stakeholders to define analytical requirements and measurable success criteria.
• Create dashboards, reports, and data visualizations that communicate operational performance and model results clearly.
• Conduct root-cause analyses related to production losses, downtime, scrap, rework, throughput, cycle time, and process variation.
• Develop and monitor key performance indicators, including overall equipment effectiveness (OEE), first-pass yield, schedule attainment, capacity utilization, downtime, scrap rate, and inventory accuracy.
• Deploy analytical models and establish processes for monitoring model performance, data quality, and business impact.
• Document data sources, methodologies, assumptions, model limitations, and technical processes.
• Promote data literacy and analytical best practices across manufacturing and operations teams.
• Ensure analytical solutions comply with applicable data governance, security, quality, and regulatory requirements.

Qualifications

Required Qualifications

• SoCal residents strongly preferred with ability to travel occasionally
• Bachelor's degree in data science, statistics, mathematics, computer science, engineering, operations research, or a related quantitative field.
• 3+ years of professional experience in data science, advanced analytics, machine learning, operations analytics, or a closely related field.
• 2+ years of experience working with ERP systems and associated operational data, such as production orders, bills of materials (BOMs), routings, inventory, procurement, material movements, costing, or capacity planning.
• 2+ years of experience working with business intelligence tools like Power BI, Tableau, and Looker
• Ability to translate ambiguous / broad objectives into a set of clearly defined problems
• Strong written, verbal, and visual communication skills.
• Fluency in Python, including experience with common data science and machine-learning libraries such as pandas, NumPy, scikit-learn, or equivalent tools.
• Fluency in SQL, including the ability to write complex queries, joins, common table expressions, window functions, aggregations, and data-quality checks.
• Demonstrated experience preparing, cleaning, joining, and analyzing large datasets from multiple systems.
• Experience applying statistical analysis, machine learning, forecasting, optimization, or anomaly-detection techniques to business or operational problems.
• Strong understanding of data validation, model evaluation, experimental design, and statistical reasoning.
• Ability to collaborate effectively with both technical teams and manufacturing stakeholders.

Preferred Qualifications

• 3+ years of experience working in a manufacturing, industrial, automotive, aerospace, medical-device, consumer-products, chemical, semiconductor, or similar production environment.
• Knowledge of manufacturing concepts such as Lean manufacturing, Six Sigma, statistical process control, overall equipment effectiveness, process capability, and root-cause analysis.
• Working experience with Git, dbt, and LLM APIs

Above and Beyond Qualifications

• 2+ years of experience working in a fast-paced startup / growth-stage environment
• Experience deploying production-grade AI-based workflow automations
• 3+ years of experience working as Industrial / Manufacturing engineer

ITAR

This role involves access to technical data and/or hardware subject to U.S. export control laws and regulations, including the International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR). In order to comply with these laws, employment is contingent upon verifying your status as a "U.S. Person" as defined by 22 C.F.R. * 120.15, or obtaining any required government authorization.

Compensation

In compliance with all states and cities requiring transparency of pay, the expected pay range for this position is $100,000 - $135,000.

Compensation can vary depending on several factors, including a candidate's qualifications, skills, experience, competencies, and geographic location. Some roles may qualify for extra incentives like equity, commissions, or other variable performance-related bonuses. Further details will be provided by our recruiting team during the interview process.

Benefits

Benefit offerings include Medical Insurance and Prescription Drugs, Dental Insurance, Vision Insurance, Flexible Spending Accounts, Life Insurance, Short-Term Disability, Long-Term Disability Insurance (for eligible employees), Employee Assistance Plan (EAP), Paid Time Off (may include vacation and sick time), Retirement Program, and Other Voluntary Benefits.