Remote Manufacturing Data Scientist: Predictive Analytics

Allfast Fastening Systems; California (MO); On-site; USD 100,000 - 135,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Flexible Spending Accounts

Life Insurance

Short-Term Disability

Long-Term Disability Insurance

Employee Assistance Plan (EAP)

Paid Time Off

Retirement Program

Other Voluntary Benefits

Job summary

Allfast Fastening Systems LLC is seeking a Manufacturing Data Scientist to transform complex operational data into actionable insights that improve productivity, quality, and supply-chain performance. You will partner with manufacturing, engineering, quality, and IT teams to develop analytical solutions and communicate findings to both technical and nontechnical stakeholders.

The ideal candidate has strong Python and SQL expertise, experience with ERP data, and a practical understanding of

Qualifications

• Bachelor’s degree in data science, statistics, mathematics, computer science, engineering, OR related field.
• 3+ years in data science or analytics.
• 2+ years with ERP systems and related production data (orders, BOMs, inventory).
• 2+ years with Power BI, Tableau, and Looker.
• Strong written, verbal, and visual communication skills.
• Fluency in Python and SQL for data cleaning and modeling.
• Ability to translate complex objectives into clearly defined analytics problems.

Responsibilities

• Analyze manufacturing data to identify trends, risks, inefficiencies, and improvements.
• Build data pipelines using SQL and Python.
• Develop predictive and prescriptive models for equipment reliability and planning.
• Integrate data from ERP, MES, quality systems, and sensor data.
• Create dashboards and reports communicating performance and model results.
• Conduct root-cause analyses for downtime, scrap, and throughput.
• Monitor KPIs like OEE, yield, and inventory accuracy.
• Ensure data governance and regulatory compliance.

Skills

Python

SQL

Analytical thinking

Communication

Collaboration

Education

Bachelor’s degree in data science, statistics, mathematics, computer science, engineering, OR related field

Tools

Power BI

Tableau

Looker

Git

dbt

Job description

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

Main Duties & Responsibilities

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.