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Metadata Library Jobs in Philadelphia, PA (NOW HIRING)

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Clinical Data Standard Consultant

Blue Bell, PA · On-site +1

Responsible for the implementation, strategy, and configuration of a metadata repository used to manage libraries of CDISC related metadata, terminology and related standards. Mentor Clinical Data ...

Dorman Products

Data Engineering Lead

Colmar, PA · Hybrid

$113K - $136K/yr

... libraries) * Support existing HANAbased data models and integrations while modern cloud ... Implement data quality checks, lineage, and metadata standards * Develop data validation frameworks ...

Dorman Products, Inc.

Data Engineering Lead

Colmar, PA · On-site

$113K - $136K/yr

... libraries) * Support existing HANA-based data models and integrations while modern cloud ... Implement data quality checks, lineage, and metadata standards * Develop data validation frameworks ...

Dorman Products

Data Engineering Lead

Colmar, PA · Hybrid

$113K - $136K/yr

... libraries) * Support existing HANA‑based data models and integrations while modern cloud ... Implement data quality checks, lineage, and metadata standards * Develop data validation frameworks ...

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All JobsMetadata Library JobsMetadata Library Jobs in Philadelphia, PA

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How much do metadata library jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for metadata library in Philadelphia, PA is $18.85, according to ZipRecruiter salary data. Most workers in this role earn between $15.29 and $21.35 per hour, depending on experience, location, and employer.

What are metadata librarians and what do they do?

Metadata librarians are information professionals who manage and organize metadata, which is data that describes other data, for library collections. They create, edit, and maintain metadata records to ensure resources are discoverable, accessible, and properly described in library catalogs and digital repositories. Their work supports searchability, digital preservation, and resource sharing by applying standards and best practices for cataloging. Metadata librarians often collaborate with IT staff, archivists, and subject specialists to enhance user access to library materials.

What is the difference between Metadata Library vs Metadata Specialist?

AspectMetadata LibraryMetadata Specialist
CredentialsTypically requires a degree in library science, information management, or related fieldsRequires similar credentials, often with additional certifications in data management or information systems
Work EnvironmentLibraries, archives, or information centers managing large metadata collectionsData-driven organizations, digital repositories, or information management teams
Employer & IndustryLibraries, museums, archives, academic institutionsTech companies, publishing, digital content providers
Search & Comparison IntentUnderstanding library metadata management rolesSpecialized data and metadata management tasks

The main difference is that a Metadata Library focuses on managing metadata within library and archival settings, while a Metadata Specialist handles metadata in broader digital and data environments. Both roles require similar credentials but serve different industry needs.

What are some common challenges faced by professionals working in a metadata library role, and how can they be addressed?

Professionals in a metadata library role often encounter challenges such as maintaining consistency and accuracy in metadata standards across diverse collections, keeping up with evolving cataloging guidelines, and integrating new technologies or platforms. Addressing these challenges typically involves ongoing training, collaboration with colleagues to develop clear metadata policies, and staying informed about industry best practices. Regular communication with IT teams and subject specialists is also key to ensuring that metadata effectively supports discoverability and access for library users.

What are the key skills and qualifications needed to thrive as a Metadata Librarian, and why are they important?

To thrive as a Metadata Librarian, you need expertise in cataloging standards (such as MARC, Dublin Core), metadata schema, and information organization, usually supported by a Master's in Library Science or a related field. Familiarity with integrated library systems (ILS), metadata management tools, and knowledge of cataloging software like OCLC Connexion is typical. Attention to detail, analytical thinking, and strong communication skills help ensure accuracy and facilitate collaboration with library staff. These skills and qualities are crucial to maintaining accessible, well-organized digital and print collections that support user discovery and research.
What are popular job titles related to Metadata Library jobs in Philadelphia, PA? For Metadata Library jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Metadata Library jobs in Philadelphia, PA look for? The top searched job categories for Metadata Library jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Metadata Library jobs? Cities near Philadelphia, PA with the most Metadata Library job openings:
Metadata Library jobs near you
Infographic showing various Metadata Library job openings in Philadelphia, PA as of June 2026, with employment types broken down into 60% Full Time, 20% Part Time, and 20% Contract. Highlights an 100% In-person job distribution, with an average salary of $39,212 per year, or $18.9 per hour.
Senior Applied Data Scientist - Data Architecture & Feature Engineering

Senior Applied Data Scientist - Data Architecture & Feature Engineering

Keysight Technologies, Inc.

Harrisonville, NJ

Other

Posted 18 days ago

Keysight Technologies rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

40th of 139 rated electronics manufacturers

Job description

Overview

Keysightis on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn moreabout what we do. 

Our award-winningculture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions.We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.


About Keysight AI Labs

Keysight’s AI Labs is a global R&D group pioneering the integration of machine learning, generative AI into Keysight’s test, measurement, and design solutions. Our mission is to transform how engineers design, simulate, and validate advanced systems - from 6G and semiconductors to quantum and automotive - by embedding AI throughout our workflows.

About the AI Team 

Join Keysight's central AI Hub in the heart of Barcelona. We are expanding our newly formed AI Team. As part of this growing team, you will join a vibrant, cross-functional environment that brings together experts in ML engineering, data science, physics-informed modeling, and software development. You’ll work closely with domain experts across RF, EM, circuit design, and test & measurement to accelerate scientific innovation through AI.

About the Role

We are seeking a Senior Applied Data Scientist with strong data engineering capabilities. You will explore complex engineering data, architect scalable data infrastructure, and shape the data foundation powering AI model development across Keysight products. This role bridges research and production, from data discovery to robust ETL/ELT pipeline design and feature creation for ML models.


Responsibilities

  • Partner with internal experts to identify critical data sources and define ML-relevant features

  • Architect and build scalable data lakes/databases for standardized and efficient cross-org data access

  • Clean, align, normalize, and integrate data from simulations, measurements, and operational systems

  • Develop and maintain reproducible ETL/ELT pipelines for structured and unstructured data using SQL, Python, Snowflake, and cloud-native workflows

  • Perform EDA, feature engineering, regression, and dimensionality reduction to generate high-value insights

  • Ensure data governance, lineage, metadata management, and compliance

  • Support experiment design, hypothesis testing, and statistical modeling

  • Work closely with ML engineers to accelerate model training, deployment, and ongoing monitoring

  • Present results and actionable recommendations to product and R&D stakeholders


Qualifications

Required Qualifications

  • Master’s in Data Science, Statistics, CS, EE, or related quantitative field

  • 5+ years of experience as an applied data scientist or hybrid DS/DE role

  • Expert proficiency in Python, SQL, and data manipulation libraries

  • Strong background in statistics, algorithms, and data structures

  • Experience with relational + NoSQL databases and designing scalable data architectures

  • Hands-on experience with big data tools (e.g., Spark, Kafka, Snowflake, Databricks, Hadoop)

  • Experience supporting ML workflows — MLOps, CI/CD, containerization (Docker/Kubernetes)

  • Experience with cloud platforms: Azure / AWS / GCP

  • Clear track record of driving data-to-value outcomes

Desired Qualifications

  • Experience with measurement or simulation-heavy domains (e.g., wireless, electronics, semiconductor)

  • Familiarity with deep learning frameworks and ML for time-series or unstructured data

  • Visualization skills (e.g., Power BI, Tableau, Plotly)

  • Knowledge of data governance, lineage, metadata management tools

  • Experience with microservices and APIs

  • Open-source contributions or publications

Careers Privacy Statement***Keysight is an Equal Opportunity Employer.*** 

Qualifications:

Required Qualifications

  • Master’s in Data Science, Statistics, CS, EE, or related quantitative field

  • 5+ years of experience as an applied data scientist or hybrid DS/DE role

  • Expert proficiency in Python, SQL, and data manipulation libraries

  • Strong background in statistics, algorithms, and data structures

  • Experience with relational + NoSQL databases and designing scalable data architectures

  • Hands-on experience with big data tools (e.g., Spark, Kafka, Snowflake, Databricks, Hadoop)

  • Experience supporting ML workflows — MLOps, CI/CD, containerization (Docker/Kubernetes)

  • Experience with cloud platforms: Azure / AWS / GCP

  • Clear track record of driving data-to-value outcomes

Desired Qualifications

  • Experience with measurement or simulation-heavy domains (e.g., wireless, electronics, semiconductor)

  • Familiarity with deep learning frameworks and ML for time-series or unstructured data

  • Visualization skills (e.g., Power BI, Tableau, Plotly)

  • Knowledge of data governance, lineage, metadata management tools

  • Experience with microservices and APIs

  • Open-source contributions or publications

Careers Privacy Statement***Keysight is an Equal Opportunity Employer.*** 

Education:UNAVAILABLEEmployment Type: UNAVAILABLE

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