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Semantic Jobs in New York (NOW HIRING)

Cyber Sphere LLC

Semantic Data AI Engineer

Manhattan, NY · On-site

$126K - $151K/yr

Semantic Data & AI Engineer Location: Remote Duration:4+Months Note: Work as part of the Client delivery team supporting Life & Annuity clients with initiatives related to agent licensing ...

New

1 point system

Semantic Markup Analyst

New York, NY · Remote

We're looking for a Senior Business Analyst to support semantic markup (i.e., evaluating and maintaining our markup standards--and focused in particular on changes we may need to support non-book ...

AEG

Principal AI/ML Engineer, Semantic Data

Manhattan, NY · On-site

$235K - $260K/yr

The Principal AI/ML Engineer, Semantic Data will design and build the semantic intelligence layer that enables consistent understanding of fan data, business concepts, and operational workflows ...

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All JobsSemantic JobsSemantic Jobs in New York

Semantic information

See New York salary details

$60.7K

$129.8K

$189.8K

How much do semantic jobs pay per year?

As of Sep 4, 2026, the average yearly pay for semantic in New York is $129,833.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $146,100.00 per year, depending on experience, location, and employer.

What is a semantic job?

A Semantic job typically involves working with meaning and context in language, data, or technology. It may include roles in natural language processing (NLP), knowledge representation, search engine optimization (SEO), or semantic web technologies. Professionals in this field develop algorithms, ontologies, and models to improve understanding and classification of information. These jobs are common in AI, data science, and digital marketing industries.

What are the key challenges faced by semantic engineers when implementing knowledge graphs in large organizations?

Semantic Engineers often encounter challenges related to integrating disparate data sources, ensuring data quality, and aligning ontologies across departments. In large organizations, there can be legacy systems and inconsistent data formats, making it difficult to create a unified semantic model. Additionally, Semantic Engineers must collaborate closely with data architects, subject matter experts, and software developers to ensure the knowledge graph accurately reflects the organization's information needs and remains scalable as requirements evolve.

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

To thrive as a Semantic Analyst, you need expertise in linguistics, natural language processing (NLP), data analysis, and a relevant degree such as linguistics, computer science, or information science. Familiarity with tools like Python, NLP libraries (e.g., NLTK, spaCy), and semantic annotation systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex language data and collaborate with technical teams. These competencies are vital to accurately extract, structure, and apply meaning from language data, driving insights and solutions in various industries.

What is the difference between Semantic vs Data Analyst?

AspectSemanticData Analyst
Required CredentialsBackground in linguistics, computer science, or related fields; knowledge of semantic web technologiesDegree in statistics, mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentResearch-focused, often in tech or AI companies, working on language understandingBusiness or research settings, analyzing data to inform decisions
Industry UsageUsed in AI, NLP, and semantic web projectsUsed across finance, marketing, healthcare, and other sectors
Common Search/ComparisonSemantic vs Data Analyst

Semantic professionals focus on understanding and structuring meaning in language and data, often working with AI and NLP technologies. Data Analysts interpret data sets to generate insights for business decisions. While both roles involve data, Semantic roles emphasize language and knowledge representation, whereas Data Analysts focus on statistical analysis and reporting.

What are the most commonly searched types of Semantic jobs in New York?

The most popular types of Semantic jobs in New York are:

What are popular job titles related to Semantic jobs in New York?

For Semantic jobs in New York, the most frequently searched job titles are:

What job categories do people searching Semantic jobs in New York look for?

The top searched job categories for Semantic jobs in New York are:

Semantic jobs near you
Infographic showing various Semantic job openings in New York as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 73% Physical, 6% Hybrid, and 21% Remote job distribution, with an average salary of $129,833 per year, or $62.4 per hour.

Director, Semantic & Knowledge Engineering

Novartis Pharmaceuticals Corporation

East Hanover, NJ • Hybrid

$194K - $361K/yr

Full-time

Medical, Retirement, PTO

Posted 12 days ago

Job description

Band

Level 6


Job Description Summary

#LI-Hybrid
Reporting to the Executive Director, Semantic and Knowledge Engineering, the Director, Semantic and Knowledge Engineering leads the design, implementation, and governance of enterprise semantic models, ontologies, knowledge graphs, and metadata frameworks that power NovaOS. This role partners across Applied AI, Data Science, Product, and Engineering to establish trusted semantic assets that enable interoperable data, AI reasoning, retrieval-augmented generation (RAG), and scalable enterprise intelligence.
The ideal location for this role is East Hanover but remote work may be possible (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. If associate is remote, all home office expenses and any travel/lodging to specific East Hanover for periodic live meetings will be at the employee's expense. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 10% travel.


Job Description

Key Responsibilities:

  • Lead the design and implementation of enterprise ontologies, taxonomies, businessvocabularies, and semantic models.

  • Develop andmaintainknowledgegraphs and semantic services that support AI, analytics, search, and business applications.

  • Partner with AI, Data Science, Product, and Engineering teams to integrate semantic capabilities intoNovaOSproducts and platforms.

  • Establish metadata standards, semantic governance processes, and quality controls for enterprise knowledge assets.

  • Support AI initiatives by developing semantic foundations for RAG, agentic AI, reasoning engines, and contextual search.

  • Evaluate emerging semantic technologies and recommend improvements to the enterprise knowledge architecture.

  • Lead and mentor semantic and knowledge engineers while promoting reusable engineering patterns and technical excellence.

Essential Requirements:

  • Education:Bachelor'sor advanced degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, ora relateddiscipline.

  • 8+ years of experience in semantic technologies, knowledge engineering, metadata management, or enterprise information architecture.

  • Hands-onexpertisewith ontologies, RDF/OWL, knowledge graphs, graph databases, metadata management, and semantic web technologies.

  • Experience implementing semantic solutions that enable AI, analytics, interoperability, and enterprise search.

  • Strong leadership, communication, and stakeholder management skills with experience leading cross-functional technical initiatives.

Desirable Requirements:

  • Experience applying semantic technologies to generative AI, agentic AI, RAG, and enterprise AI platforms.
  • Experience in pharmaceutical, healthcare, or other highly regulated industries.

Novartis Compensation Summary:

The salary for this position is expected to range between $194,600 and $361,400 per year.

The final salary offered isdeterminedbased on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health,lifeand disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days,holidaysand other leaves.


EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.


Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to tas.nacomms@novartis.com call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings


Salary Range

$194,600.00 - $361,400.00


Skills Desired

Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Stakeholder Engagement, Statistical Analysis, Time Series Analysis

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