Manufacturing Data Scientist

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

Main Duties & Responsibilities

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.