Synthetic Job Descriptions Dataset – Tech & Non-Tech Roles (2025)

This dataset contains 1,100 synthetic job descriptions (JDs) spanning 55 diverse roles, designed to facilitate career guidance, resume building, ATS (Applicant Tracking System) simulation, and research in NLP/ML.

All job descriptions are synthetically generated based on curated references from publicly available job postings, career guides, and professional role descriptions. They are not real job postings but represent realistic expectations, responsibilities, and skills for each role.

Roles Covered

Tech Roles (Core, Popular, and Niche)

1. Software Engineer
2. Software Developer
3. Full Stack Developer
4. Backend Developer
5. Frontend Developer
6. Data Scientist
7. Machine Learning Engineer
8. AI Engineer
9. DevOps Engineer
10. Cloud Engineer
11. Data Analyst
12. Business Intelligence Analyst
13. QA Engineer
14. Test Automation Engineer
15. iOS Mobile App Developer
16. Android Mobile App Developer
17. Vibe Coder
18. UI Designer
19. UX Designer
20. Product Designer
21. Cybersecurity Analyst
22. Python Developer
23. Data Engineer
24. Network Engineer
25. Cloud Architect
26. Systems Engineer
27. Java Developer
28. .NET Developer
29. Web Developer
30. Software Tester (SDET)
31. Solutions Architect
32. Big Data Specialist
33. Fintech Engineer
34. AI Prompt Engineer
35. Blockchain Developer
36. Robotics Engineer
37. Javascript Developer
38. AR/VR Developer
39. IoT Engineer
40. Ethical Hacker
41. Site Reliability Engineer (SRE)
42. Game Developer

Non-Tech Roles (Business, Creative, Operations, and Niche)

1. Product Manager
2. Project Manager
3. Marketing Specialist
4. Digital Marketing Specialist
5. SEO Specialist
6. Content Writer
7. Copywriter
8. Business Analyst
9. Operations Manager
10. Sales Executive
11. Technical Writer
12. Market Research Analyst
13. Graphic Designer

Dataset Structure

• Total Job Descriptions: 1,100 (20 per role)
• Fields per JD:

Key Features & Insights

• Balanced Experience Distribution: ~50% entry-level / fresher, ~50% experienced / senior roles.
• Top Skills Across Roles: Python, JavaScript, React, TensorFlow, ML/NLP, Docker, Collaboration, Problem-solving, Figma.
• Keyword Trends: AI, ML, Data Analytics, Cloud, DevOps, Prompt Engineering, UX/UI.
• Comprehensive Coverage: Tech roles cover core development, data, AI, cloud, security, and niche specialties, while non-tech roles cover business, creative, operations, marketing, and analytics.

Potential Use Cases

• Resume Builders: Generate role-specific resumes highlighting relevant skills and responsibilities.
• ATS Simulation / Scoring: Test applicant tracking systems with realistic job descriptions.
• Career Analytics: Analyze trends in skills, responsibilities, and popular roles.
• Machine Learning & NLP Projects: Use for text classification, skill extraction, recommendation systems, and job matching.
• Educational Purposes: Ideal for learning about job role requirements across tech and non-tech domains.

File Formats

• JSON: job_dataset.json – structured array of job objects.
• CSV: job_dataset.csv – arrays flattened with semicolons for easy viewing in Excel or Pandas.

Licensing

• Free to use, share, and adapt for research, educational, or personal projects.
• Please cite the dataset in publications or projects:

Synthetic Job Descriptions Dataset (2025) – Curated & Generated by Aditya Raj Srivastava (https://www.kaggle.com/adityarajsrv)

PredictLeads Global Technographic Dataset delivers in-depth insights into technology adoption across millions of companies worldwide. Our dataset, sourced from HTML, JavaScript, and job postings, enables B2B sales, marketing, and data enrichment teams to refine targeting, enhance lead scoring, and optimize outreach strategies. By tracking 48,000+ technologies across 98M+ websites, businesses can uncover market trends, assess competitor technology stacks, and personalize their approach.

Use Cases:

✅ Enhance CRM Data – Enrich company records with detailed real-time technology insights. ✅ Targeted Sales Outreach – Identify prospects based on their tech stack and personalize outreach. ✅ Competitor & Market Analysis – Gain insights into competitor technology adoption and industry trends. ✅ Lead Scoring & Prioritization – Rank potential customers based on adopted technologies. ✅ Personalized Marketing – Craft highly relevant campaigns based on technology adoption trends.

API Attributes & Structure:

• id (string, UUID) – Unique identifier for each technology detection.
• first_seen_at (ISO 8601 date-time) – Timestamp when the technology was first detected on the company's website.
• last_seen_at (ISO 8601 date-time) – Most recent timestamp when the technology was last observed.
• behind_firewall (boolean) – Indicates whether the technology is protected behind a firewall.
• score (float, 0–1) – Confidence score for the detection accuracy.
• company (object) – The company using the detected technology, including:
• - id (UUID) – Unique company identifier.
• - domain (string) – Company website domain.
• - company_name (string) – Company's official name.
• - ticker (string, nullable) – Stock ticker (if publicly listed).
• technology (object) – Information on the detected technology, including:
• - id (UUID) – Unique technology identifier.
• - name (string) – Technology name (e.g., Salesforce, HubSpot, AWS).
• seen_on_job_openings (boolean) – True/False flag indicating if the technology is - mentioned in job postings.
• seen_on_subpages (array of objects) – List of company subpages where the technology was detected.

📌 PredictLeads Technographic Data is trusted by enterprises and B2B professionals for accurate, real-time technology intelligence, enabling smarter prospecting, data-driven marketing, and competitive analysis

PredictLeads Technology Detections Dataset https://docs.predictleads.com/v3/guide/technology_detections_dataset

Comprehensive business intelligence analysis for D3.js including financial metrics, founder insights, competitive positioning, and investment research. This dataset contains AI-powered analysis of leadership interviews, public content, and market intelligence for due diligence and competitive research purposes.

In 2023, the tech skill most in demand by recruiters was web development. This was closely followed by DevOps and database software skills. Interestingly, over ** percent of recruiters were actively seeking individuals with cybersecurity skills. Not far behind, AI/Machine learning/Deep learning ranked fourth, with approximately ** percent of respondents identifying it as their most sought-after tech skill. These preferences align with the skills that developers worldwide are keen to acquire, particularly web development and AI/Machine learning/Deep learning. AI at the forefront of IT skills Since the release of ChatGPT in late 2022, demand for AI and automation skills has increased across all sectors. In 2023, ChatGPT was the leading technology skill globally according to topic consumption on Udemy Business, experiencing a massive growth of over ***** percent in global topic consumption. In the same year, over ** percent of software developers reported using AI to help write code in the development workflow, while another ** percent said they currently use it for debugging code. Different languages for different needs JavaScript and Java, commonly used for back-end and front-end web development, were the most demanded programming languages worldwide in 2022, followed by SQL and Python. By industry, JavaScript and Java hold the fort in the IT services and aviation industries, while SQL was more popular in the healthcare sector as well as the marketing and advertising industries. Python, well suited for data science applications, was more commonly used in the manufacturing, education, and energy industries.