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Research Semantic Analysis Jobs (NOW HIRING)

NEC Labs

ML - Researcher

Princeton, NJ

A lot of our research has been translated into NEC's businesses, leading to innovative products and services of NEC, such as semantic analysis of job applications and product reviews, accident ...

NEC Labs America

ML - Researcher

Princeton, NJ · On-site

$150K - $180K/yr

A lot of our research has been translated into NEC's businesses, leading to innovative products and services of NEC, such as semantic analysis of job applications and product reviews, accident ...

Aimpoint Digital

$97K - $128K/yr

Aimpoint Digital is a market-leading data, AI, and operations research advisory and solution ... You will work across modern data engineering, AI engineering, agentic workflows, semantic analytics ...

Revel

Compiler Engineer

Los Angeles, CA

Implement advanced compiler techniques including parsing, semantic analysis, intermediate ... Engage in research and development activities, contributing innovative solutions to complex ...

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Research Semantic Analysis information

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$111.5K

$206K

How much do research semantic analysis jobs pay per year?

As of Jun 7, 2026, the average yearly pay for research semantic analysis in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Research Semantic Analyst, and why are they important?

To thrive as a Research Semantic Analyst, you need expertise in linguistics, data analysis, and a strong understanding of semantics, typically supported by a degree in linguistics, computer science, or a related field. Familiarity with natural language processing (NLP) tools, semantic annotation platforms, and data analysis software like Python or R is commonly required. Strong analytical thinking, attention to detail, and effective communication are essential soft skills in this role. These competencies are crucial for accurately interpreting and modeling language data, ensuring high-quality research outcomes and actionable insights.

What is the difference between Research Semantic Analysis vs Data Analyst?

AspectResearch Semantic AnalysisData Analyst
Required CredentialsTypically requires a degree in linguistics, computer science, or related fields; knowledge of NLP and semantic modelsUsually requires a degree in statistics, mathematics, or related fields; proficiency in data visualization and statistical tools
Work EnvironmentResearch labs, tech companies, academic institutions focusing on language and AI projectsBusiness environments, consulting firms, or corporate data teams analyzing large datasets
Industry UsageUsed in natural language processing, AI development, and linguistic researchApplied in marketing, finance, healthcare, and other sectors for data-driven decision making

Research Semantic Analysis focuses on understanding and modeling language meaning using NLP techniques, often in research or AI development. Data Analysts interpret and visualize data to inform business decisions. While both roles involve data and analysis, their tools, goals, and industries differ significantly.

How does collaboration typically work for professionals in Research Semantic Analysis?

In Research Semantic Analysis, collaboration is essential and often involves working closely with interdisciplinary teams, including data scientists, linguists, software engineers, and subject matter experts. Professionals in this role frequently participate in brainstorming sessions, share findings, and integrate feedback to enhance semantic models or algorithms. Effective communication and the ability to translate complex concepts across different expertise areas are crucial for success. Regular meetings and collaborative platforms help ensure alignment on project goals and facilitate continuous learning.

What is research semantic analysis?

Research semantic analysis is the process of examining and interpreting the meanings of words, phrases, and concepts within research documents or datasets. It involves using computational and linguistic techniques to analyze the relationships, context, and patterns of language to extract insights or identify trends. This method is commonly used in fields like linguistics, data science, and information retrieval to improve understanding of large volumes of unstructured text.

ML - Researcher

NEC Labs

Princeton, NJ

Other

Posted 28 days ago

Job description

The Machine Learning Department, NEC Laboratories America has openings for researchers with a passion for developing the next generation of machine intelligence. Expertise in machine learning with a proven track record of original research are prerequisites for this position.The Machine Learning Department has been at the forefront of research in such areas as deep learning, statistical learning, and machine reasoning for almost two decades. The research in our department has been published in premier venues and has won numerous awards, including the 2010 IEEE Neural Networks Pioneer Award, the 2012 IEEE Frank Rosenblatt Award, the 2012 Benjamin Franklin Medal, the 2013 NEC C&C Prize, ICML 2018 Test of Time Award, and NeurIPS 2018 Test of Time Award

Our recent work has been published at NeurIPS, ICML, ICLR, CVPR, KDD, ACL, RECOMB, Nature, Nature Genetics, Nature Machine Intelligence, and other top venues, and has garnered media coverage (Science News, Nature News, New York Times, MIT Technology Review).A lot of our research has been translated into NEC's businesses, leading to innovative products and services of NEC, such as semantic analysis of job applications and product reviews, accident prevention, anomaly detection, and digital pathology. Currently our department is tackling challenges in imparting abstract reasoning capabilities to machine learning and facilitating effective human-machine collaboration, and how these enable new applications in sustainable environment, smart manufacturing, safe cities, natural language processing, and personalized healthcare.https://www.nec-labs.com/research/machine-learning/home/

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