ZipRecruiter

Log In

1

Scientific Machine Learning Jobs in Lancaster, PA

Hersheys

Staff Engineer OT Digital Systems

Hershey, PA · On-site

Required: * Bachelor's degree in Engineering, Computer Science, or related field * 5+ years of ... Familiarity with analytics, machine learning, and AI platforms; Databricks preferred * Experience ...

previous pagenext page

Showing results 21-40

All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Lancaster, PA

Scientific Machine Learning information

See Lancaster, PA salary details

$13

$30

$50

How much do scientific machine learning jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for scientific machine learning in Lancaster, PA is $30.59, according to ZipRecruiter salary data. Most workers in this role earn between $18.70 and $38.99 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Lancaster, PA?

For Scientific Machine Learning jobs in Lancaster, PA, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Lancaster, PA look for?

The top searched job categories for Scientific Machine Learning jobs in Lancaster, PA are:

What cities near Lancaster, PA are hiring for Scientific Machine Learning jobs?

Cities near Lancaster, PA with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you

Systems Integrations Analyst

Graham Packaging Company

Lancaster, PA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 11 days ago

Graham Packaging rating

7.0

Company rating: 7.0 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

69th of 120 rated packaging manufacturers

Job description

Company Statement
Graham Packaging is a people, planet and values-based company and a leader in sustainable packaging manufacturing. From the kitchen to the laundry room, Graham Packaging is part of your everyday life.
For employees at Graham, our Blue Culture is part of their everyday lives, too. In other words, Blue is how we do things here.
At Graham, we are united by a clear vision. We know our part and help those around us know theirs, encouraging one another to continuously improve. We create a safe, challenging environment to innovate by supporting creative ideas and new ways of thinking. We take the initiative to cultivate our individual growth and help others do the same, while keeping ourselves and one another accountable. And we actively promote cooperation, collaboration, integrity and respect across regions and teams to foster an engaged, diverse and connected workforce.
We value our employees, and a Blue Culture allows for the most rewarding employee experience as part of the Graham family. Blue is how we feel about what we do-together-to create a better tomorrow. Working at Graham means you lead constructively with clear goals, use diverse thinking to drive excellence, accountability, innovation, as well as demonstrating collaboration, embracing learning, and taking action for continuous improvement and growth.
Overview
Graham Packaging is a leading North American manufacturer of rigid plastic containers, operating 270+ production lines across facilities throughout the US. Our manufacturing intelligence team connects real-time machine data, quality systems, and business applications into a unified data platform that drives measurable bottom-line returns.
We are hiring a Systems Integration Analyst to help deliver the next phase of that platform: integrating our production and quality data systems to enable AI-driven analytics. This is hands-on integration work; building API connections, moving data between industrial and enterprise systems, and working across IT and OT teams to make disconnected systems talk to each other.
You will work directly with our AI and analytics initiatives as part of the team. The integrations you build are what make our AI projects possible, and as the data foundation matures, you will have a direct path into applied AI and machine learning work.
Responsibilities
Integration Development
  • Build and maintain API integrations connecting industrial data platforms, quality databases, SQL data stores, and enterprise business systems
  • Write Python scripts and services to extract, transform, and move production and quality data reliably between systems
  • Develop and test data pipelines with proper error handling, logging, and documentation so they run without babysitting
  • Troubleshoot integration failures across the full path: source system, network, credentials, transformation logic, destination
Cross-Functional IT/OT Coordination
  • Work with corporate IT teams on service accounts, database access, firewall rules, and infrastructure requests.
  • Work with plant-side OT and controls resources to understand data sources at the machine and line level
  • Navigate the boundary between enterprise IT standards and plant-floor realities, and know when each applies
  • Document system interfaces, data flows, and access requirements for audit and team continuity
AI Project Support
  • Partner with the team's AI and analytics engineers to deliver the data foundations their models depend on
  • Prepare, structure, and validate datasets used in machine learning projects targeting quality prediction and process improvement
  • Grow your applied AI skills through direct project involvement, model deployment support, results validation, and pipeline automation
  • Contribute ideas: as part of the team you will help develop the specifications and support users
Team Execution
  • Take direction from senior integration engineers and deliver assigned workstreams with minimal rework
  • Participate in plant visits to see production systems firsthand and validate integrations against real operations
  • Communicate progress, blockers, and risks clearly

Qualifications
Qualifications
Required
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field - or equivalent demonstrated experience
  • 2-6 years of hands-on experience building integrations, data pipelines, or system-to-system connections in Python (internships and co-ops in operational environments count)
  • Demonstrated experience working with REST APIs and SQL databases in real projects, not just coursework
  • Experience working in or with operational/industrial environments, or clear evidence of the systems mindset those environments require
  • Willingness to travel to manufacturing plant sites periodically (estimated 10-20%)

Preferred
  • Direct manufacturing, industrial, utilities, logistics, or similar operational-environment experience
  • Familiarity with industrial data platforms (historians, MES) or industrial communication protocols
  • Exposure to machine learning workflows: data preparation, feature engineering, or model deployment support
  • Experience navigating enterprise IT processes: access requests, change management, security reviews

Skills
Required
  • Python: Solid working proficiency: requests, pandas, working with JSON/XML, writing scripts that run unattended; this is the core tool of the job
  • APIs & Integrations: Hands-on experience calling and consuming REST APIs; understanding of authentication methods (API keys, OAuth, service accounts); experience connecting systems that were not designed to talk to each other
  • SQL & Databases: Comfortable querying and writing to relational databases; understanding of schemas, joins, and data types across systems
  • IT/OT Awareness: Understands that plant-floor systems are not cloud apps: legacy protocols, network segmentation, uptime constraints, and change control. Prior exposure to manufacturing, industrial, utility, or similar operational environments strongly preferred
  • Problem Solving: Debugs methodically across system boundaries; comfortable when the answer is not on Stack Overflow because the system is 15 years old
  • AI Interest: Genuine motivation to grow into applied AI and machine learning work; foundational exposure through coursework, projects, or self-study is a plus

Preferred
  • Manufacturing / OT: Direct experience in a manufacturing company or operational environment: MES, SCADA, historians, PLCs, industrial protocols (OPC-UA, Modbus), or plant-floor data systems
  • Enterprise Systems: Exposure to SAP, ERP data structures, or quality management systems
  • Visualization: Power BI or similar dashboard tooling for validating and presenting integrated data

The standard compensation for this role is $81,500 - $122,300. Salary offers will be determined based on final candidate qualifications, experience, skillset, and other relevant factors.
Compensation Statement
The expected salary range for the position described in this posting is made in accordance with the legal mandates of certain jurisdictions within the United States. The final agreed-upon compensation is based on individual qualifications and experience.
Benefits Statement
Benefits include medical, dental, vision and basic life insurance. Employees are able to enroll in the company's 401K Employee Saving Plan and may participate in its Employee Wellness Program. Employees will also receive paid time off in accordance with company policy and state law requirements.
EEO Disclaimer
Graham Packaging is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, sex (including pregnancy), sexual orientation, religion, creed, age, national origin, physical or mental disability, gender identity and/or expression, marital status, veteran status or other characteristics protected by law.

What Graham Packaging employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Graham Packaging logo

About Graham Packaging

Sourced by ZipRecruiter

Graham Packaging is a people, planet and values-based company and a leader in sustainable packaging manufacturing. From the kitchen to the laundry room, Graham Packaging is part of your everyday life. For employees at Graham, our Blue Culture is part of their everyday lives, too. In other words, Blue is how we do things here.

Industry

Plastics and rubber products manufacturing

Company size

10,000+ Employees

Headquarters location

York, PA, US

Year founded

1970

View All Graham Packaging Jobs

Apply