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Text Analytics Jobs (NOW HIRING)

Data Scientist

Windsor Mill, MD · On-site +1

$102.60K - $144.90K/yr

Proven expertise in NLP and text analytics, including transformer-based architecture (e.g., BERT and related models), embeddings, vector databases, and semantic search systems. * Hands-on experience ...

Experience with text analytics, data mining and social media analytics. * Statistical knowledge in standard techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks ...

Preferred : • Fundamental understanding around text analytics and its applications/role/use in business intelligence/business analytics (i.e. search, entity extraction, sentiment analysis, document ...

Proven expertise in NLP and text analytics, including transformer-based architecture (e.g., BERT and related models), embeddings, vector databases, and semantic search systems. * Hands-on experience ...

Free-text analytics * Machine learning (ML) algorithms * Predictive modeling and analysis * Data visualization software (Tableau preferred) * Familiarity with AWS SageMaker * Strong programming ...

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Text Analytics information

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$64.5K

$125.3K

$179K

How much do text analytics jobs pay per year?

As of May 31, 2026, the average yearly pay for text analytics in the United States is $125,326.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $149,000.00 per year, depending on experience, location, and employer.

What is a Text Analytics job?

A Text Analytics job involves extracting meaningful insights from unstructured text data using techniques like Natural Language Processing (NLP), machine learning, and statistical methods. Professionals in this field analyze text from sources such as customer reviews, social media, and documents to identify patterns, sentiment, and trends. Their work helps businesses make data-driven decisions, automate processes, and improve customer experiences. Common responsibilities include text preprocessing, developing models, and visualizing results for stakeholders.

What are the key skills and qualifications needed to thrive in the Text Analytics position, and why are they important?

To thrive in Text Analytics, you need expertise in natural language processing (NLP), data analysis, and strong programming skills in languages such as Python or R, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools like NLTK, SpaCy, TensorFlow, and data visualization platforms, as well as relevant certifications in data science or machine learning, is highly valued. Critical thinking, communication, and problem-solving abilities help professionals interpret complex textual data and convey insights to diverse audiences. These skills are important because they enable you to extract actionable information from large datasets, drive data-driven decision-making, and support organizational goals efficiently.

What are some common projects or responsibilities for professionals working in Text Analytics?

Professionals in Text Analytics often work on projects such as sentiment analysis, topic modeling, entity recognition, and document classification, drawing insights from unstructured text data. A typical day may involve leveraging machine learning algorithms, cleaning and preprocessing text datasets, and presenting findings to stakeholders via reports or dashboards. Many text analytics specialists collaborate closely with data science teams, software developers, and business analysts to integrate their work into larger products and solutions. These responsibilities not only help organizations better understand customer feedback and market trends but also enable the automation of information extraction and decision-making processes. Over time, excelling in these areas can open doors to senior data science roles, lead analyst positions, or specialized NLP research opportunities.
What cities are hiring for Text Analytics jobs? Cities with the most Text Analytics job openings:
What are the most commonly searched types of Text Analytics jobs? The most popular types of Text Analytics jobs are:
What states have the most Text Analytics jobs? States with the most job openings for Text Analytics jobs include:
Infographic showing various Text Analytics job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 38% In-person, 37% Hybrid, and 25% Remote job distribution, with an average salary of $125,326 per year, or $60.3 per hour.
Senior Data Scientist (TS/SCI)

Senior Data Scientist (TS/SCI)

Ninja Analytics

Washington, DC

Full-time

Posted 26 days ago


Job description

Senior Data Scientist (TS/SCI)

Location: Hybrid in Ashburn, VA w/telework available

Ninja Analytics is looking for a Senior Data Scientist to help lead the development and delivery of high-quality predictive modelling solutions. Successful applicants will serve as recognized subject matter experts in the application of quantitative methods, machine learning algorithms, and predictive models to address complex national and homeland security challenges. They will help our team to leverage large structured and unstructured datasets to develop and operationalize models, tools, and applications that drive optimized decision making. Project tasks include data collection, mining, data and text analytics, clustering analysis, pattern recognition and extraction, automated classification and categorization, and entity resolution to implement and enhance automated risk assessment. The products we develop provide actionable insight with real and immediate impact on the safety and security of the United States, its citizens, visitors, and economy.

The strongest applicants will offer multiple years of experience in highly dynamic, threat/risk driven operating environments. They will also have a proven track record of delivering production ready decision support tools and applications employed in the field and by mission-support entities. Applicants will have a demonstrated capacity to work closely and collaboratively with mission stakeholders; respond to emergent, mission-driven changes in priorities and expected outcomes; and apply new and emerging tools and techniques. Within three - six months of joining the project, data scientists will be expected to:

  • Perform hands-on analysis and modeling involving the creation of intervention hypotheses and experiments, assessment of data needs and available sources, determination of optimal analytical approaches, performance of exploratory data analysis, and feature generation (e.g., identification, derivation, aggregation).
  • Collaborate with mission stakeholders to define, frame, and scope mission challenges where big data interventions may offer important mitigations and develop robust project plans with key milestones, detailed deliverables, robust work tracking protocols, and risk mitigation strategies.
  • Demonstrate proficiency in extracting, cleaning, and transforming CBP transactional and mission data associated within an identified problem space to build predictive models as well as develop appropriate supporting documentation.
  • Leverage knowledge of a variety of statistical and machine learning techniques and methods to define and develop programming algorithms; train, evaluate, and deploy predictive analytics models that directly inform mission decisions.
  • Execute projects including those intended to identify patterns and/or anomalies in large datasets; perform automated text/data classification and categorization as well as entity recognition, resolution and extraction; and named entity matching.
  • Brief project management, technical design, and outcomes to both technical and non-technical audiences including senior government stakeholders throughout the model development/ project lifecycle through written as well as in-person reporting.

Qualifications

Education:

  • Bachelor’s Degree (required), Master’s or Ph.D. degree (preferred) in operations research, industrial engineering, mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.

Required Qualifications

  • 12+ years of related experience
  • Experience in developing machine learning models and applying advanced analytics solutions to solve complex business problems
  • Experience with programming languages including: R, Python, Scala, Java.
  • Proficiency with SQL programming
  • Experience constructing and executing queries to extract data in support of EDA and model development
  • Proficiency with statistical software packages including: SAS, SPSS Modeler, R, WEKA, or equivalent
  • Experience with pattern recognition and extraction, automated classification, and categorization
  • Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/ disambiguation)
  • Experience with unsupervised and supervised machine learning techniques and methods
  • Experience performing data mining, analysis, and training set construction

Desired Qualifications

  • Proficiency with Unsupervised Machine Learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc.
  • Proficiency with Supervised Machine Learning methods including Decision Trees, Support Vector Machines, Logistic Regression, Random/Rotation Forests, Categorization/Classification, Neural Nets, Bayesian Networks, etc.
  • Experience with pattern recognition and extraction, automated classification, and categorization
  • Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/ disambiguation)
  • Experience with visualization tools and techniques (e.g., Periscope, Business Objects, D3, ggplot, Tableau, SAS Visual Analytics, PowerBI)
  • Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, MapReduce, Spark, Kafka, Sqoop)

Security Clearance:

Selected applicants must be a US Citizen and able to obtain and maintain a Top Secret Security Clearance