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Text Analytics Jobs (NOW HIRING)

Mindlance

Data Scientist

San Francisco, CA · On-site

... text analytics • Predictive models to improve advertiser campaign performance • Machine learning models for categorizing web pages and content • Fraud detection & automated ranking content ...

Mindlance

Data Scientist

San Francisco, CA · On-site

... text analytics. • Predictive models to improve advertiser campaign performance • Machine learning models for categorizing web pages and content • Fraud detection & automated ranking content ...

USfalcon, Inc.

Data Scientist, Craftsman

Omaha, NE

Develop and deploy analytics solutions incorporating LLM usage, natural language processing, and text analytics. * Apply MAVEN Smart Systems to support automated decision-making, intelligent ...

USfalcon

Data Scientist, Craftsman

Fort Wayne, IN · On-site

Develop and deploy analytics solutions incorporating LLM usage, natural language processing, and text analytics. * Apply MAVEN Smart Systems to support automated decision-making, intelligent ...

Garrettgp

Data Scientist - JETARS

Fort Wayne, IN · On-site

Develop and deploy analytics solutions incorporating LLM usage, natural language processing, and text analytics. * Apply MAVEN Smart Systems to support automated decision-making, intelligent ...

USfalcon

Data Scientist, Craftsman

Omaha, NE · On-site

Develop and deploy analytics solutions incorporating LLM usage, natural language processing, and text analytics. * Apply MAVEN Smart Systems to support automated decision-making, intelligent ...

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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 Sep 11, 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?

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 does a text analytics do?

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 are the key skills and qualifications needed to thrive in text analytics?

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.

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Text Analytics jobs near you
Infographic showing various Text Analytics job openings in the United States as of September 2026, with employment types broken down into 2% Internship, 93% Full Time, 3% Part Time, and 2% Contract. Highlights an 75% Physical, 6% Hybrid, and 19% Remote job distribution, with an average salary of $125,326 per year, or $60.3 per hour.

Senior Data Analyst - Clinician Experience

Palo Alto, CA • On-site, Remote

Midi Health
Health Care and Social Assistance • 11 - 50 employees
Learn more about Midi Healthexternal

$101K - $127K/yr

Full-time

Posted 13 days ago

Key responsibilities

  • Analyze and track the clinician hiring funnel, onboarding, credentialing, and retention to identify bottlenecks and improve efficiency.

  • Design and maintain performance scorecards and dashboards to monitor operational efficiency metrics such as appointment start times and inbox turnaround times.

  • Develop scoring frameworks and evaluation logic to quantify provider attributes like empathy and clinical safety, and analyze their impact on patient retention and satisfaction.

Job description

Hybrid, Palo Alto or San Francisco (Hybrid - 2 days/week in office)
Reports to: Director Data Science + Analytics
Job Type: Full-time W2
About the Role
We are looking for a highly analytical and business-mindedSenior Data Analyst to design, build, and own the end-to-end analytical framework for our most critical operational asset: our clinician workforce. In this role, you will own the data ecosystem spanning the entire clinician lifecycle-from the moment a provider enters our recruiting funnel, through onboarding, credentialing, and state licensing, to their ongoing clinical performance, operational efficiency, and downstream business impact on patient retention.
You will develop performance frameworks that merge operational SLAs (e.g., on-time arrival, inbox turnaround times) with clinical quality and safety metrics. Additionally, you will lead our efforts in provider interaction analytics, creating evaluation and scoring logic to quantify qualitative behavioral dimensions, such as clinician empathy from consultation transcripts. Sitting at the intersection of Clinical Operations, Quality, Talent, Business Strategy, and Product, you will serve as the primary analytical partner to our Clinical Leadership and Executive team.
What You'll Do
1. Clinician Lifecycle & Funnel Analytics
  • Recruiting & Onboarding Optimization: Track and analyze the provider hiring funnel to uncover drop-off points, streamline time-to-hire, and improve conversion rates across clinical specialties.
  • Credentialing & Licensing Efficiency: Build predictive frameworks and monitoring dashboards to reduce state-by-state licensing bottlenecks and decrease provider time-to-first-consultation.
  • Cohort Retention & Attrition Modeling: Analyze first-year clinician retention trends, identifying early-warning indicators of burnout or regrettable turnover, and evaluating the long-term impact on operational capacity.
2. Operational Performance & Efficiency Metrics
  • Operational SLA Tracking: Design and maintain performance scorecards tracking operational efficiency metrics, including appointment on-time start rates, EMR/EHR inbox turnaround times, chart completion speed, and panel utilization.
3. Clinical Quality, Safety & Interaction Scoring
  • Transcript & Empathy Analytics: Establish scoring frameworks and evaluation logic to extract insights from visit transcripts. Quantify qualitative provider attributes (e.g., patient rapport, empathy, active listening) using sentiment and text analytics LLM tools.
  • Clinical Safety & Quality Alignment: Partner with the Clinical Quality and Safety teams to incorporate chart audit scores and clinical safety compliance into unified provider scorecards.
4. Downstream Patient & Business Impact
  • Clinician Impact on Patient Retention: Conduct causal and correlation analyses linking specific clinician behaviors, operational SLAs, and empathy scores directly to patient retention, net promoter scores (NPS), and long-term treatment plan adherence.
  • Executive Reporting & Strategic Guidance: Translate complex provider performance data into clear executive dashboards and strategic frameworks that directly inform clinician compensation, training programs, and operational workflows.
What You Bring
Technical Skills
  • Advanced SQL & Data Modeling: Expert-level SQL skills for querying, transforming, and modeling complex relational databases across disparate operational and EHR systems.
  • Python Proficiency: Advanced skills in Python for statistical analysis, cohort modeling, survival analysis, and text/sentiment processing.
  • Data Visualization & BI: Proven ability to design intuitive, executive-ready dashboards in modern BI tools (e.g., Looker, Tableau, PowerBI).
  • Text Analytics & NLP Awareness: Familiarity with text mining, sentiment analysis, or prompt-based LLM evaluation frameworks for processing qualitative data (transcripts, chat logs, survey notes).
  • Modern Analytics Stack & AI Tools: Experience with cloud data warehouses (Snowflake, BigQuery, Databricks) and active adoption of modern AI tools (e.g., LLMs for coding efficiency, automated insights) to accelerate analytics workflows.
Analytical & Domain Capabilities
  • Healthcare Operations Intuition: Understanding of clinical operations, provider scheduling, EMR/EHR workflows (e.g., Epic, Athena, or proprietary telehealth EHRs), and clinical quality metrics.
  • Behavioral & Lifecycle Analytics: Experience with cohort analysis, retention modeling, and constructing behavioral/qualitative scoring models.
  • Strategic Problem Structuring: Ability to take unstructured business and clinical questions and translate them into rigorous, answerable quantitative frameworks.
  • Cross-Functional Influence: Demonstrated ability to partner effectively with non-technical stakeholders, particularly Clinical Lead/Medical Directors, Operations leads, and Talent teams.
Experience
  • 5+ years of data analytics experience delivering high-impact operational or workforce insights.
  • Healthcare Experience: Strong preference for background in Digital Health, Telehealth, Tech-enabled Medical Groups, or Health Operations. (Strong candidates with backgrounds in People Analytics/People Data Science with exposure to operational telemetry are also encouraged to apply.)
  • Bachelor's or Master's degree in Quantitative discipline (Data Analytics, Health Informatics, Statistics, Industrial Engineering, Economics) or equivalent practical experience.
Interview Process:
Recruiter Screen- 30 mins
Hiring Manager Screen- 30 mins
Technical Screen- 1hr
Panel Interviews- 3 hours + Lunch in Office in Palo Alto
At this time, Midi is unable to provide visa sponsorship. Candidates must be authorized to work in the U.S. without current or future sponsorship needs.
This is a full-time W2 position. The base salary range is 150-175K and will depend on experience. Midi pays a competitive base salary, plus equity and benefits.
While you're waiting for us to review your portfolio, here's some fun content to check out
https://www.youtube.com/watch?v=1px7i6MVjNg
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At this time, Midi is unable to provide visa sponsorship. All Candidates must be authorized to work in the United States without current or future sponsorship needs.
Please note that all official communication from Midi Health will come from an @joinmidi.com email address. We will never ask for payment of any kind during the application or hiring process. If you receive any suspicious communication claiming to be from Midi Health, please report it immediately by emailing us at careers@joinmidi.com.
Midi Health is an Equal Opportunity Employer. We are committed to pay equity and ensure that all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Our compensation philosophy is based on fair, objective criteria and the impact of the role, regardless of an applicant's salary history.
Please find our CCPA Privacy Notice for California Candidates here.

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