Boolean Search Strings for Data Scientists & ML Engineers
Ready-to-use boolean strings to source Data Scientists, Machine Learning Engineers, and AI Engineers across LinkedIn, Google X-Ray, Indeed, and GitHub.
Copy-Paste Boolean Strings
("Data Scientist" OR "Machine Learning Engineer" OR "ML Engineer" OR "AI Engineer" OR "Applied Scientist") AND ("Python" OR "TensorFlow" OR "PyTorch" OR "scikit-learn") AND ("deep learning" OR "NLP" OR "computer vision" OR "LLM" OR "transformer") NOT ("intern" OR "analyst" OR "data entry") Targets ML-focused data scientists. Remove the deep learning AND clause to include traditional statistics-focused candidates.
site:linkedin.com/in/ ("Data Scientist" OR "ML Engineer" OR "Machine Learning Engineer" OR "AI Engineer") ("PyTorch" OR "TensorFlow" OR "deep learning" OR "LLM") -intern -analyst -"data entry" Great for finding passive candidates. Add university names for candidates with strong academic backgrounds.
title:("Data Scientist" OR "Machine Learning Engineer" OR "ML Engineer" OR "AI Engineer") AND (Python OR PyTorch OR TensorFlow) AND ("deep learning" OR NLP OR "computer vision") Indeed works well for data scientists actively looking. Filter by education level for PhD-required roles.
location:"United States" language:Python language:Jupyter followers:>15 repos:>10 Many data scientists publish notebooks and models on GitHub. Look for Jupyter Notebook repositories with ML project names.
Job Titles to Target
Include these title variations in your boolean strings to capture all relevant candidates.
Required Skills
Preferred Skills
Certifications
Recommended NOT Terms
Add these to your boolean string with NOT to filter out irrelevant results:
Sourcing Tips for Data Scientists
Data scientists with Kaggle profiles or competition rankings are often strong candidates. Search for 'Kaggle Master' or 'Kaggle Grandmaster' in LinkedIn profiles.
Look for published papers on arXiv or Google Scholar. Candidates who publish research tend to have deeper technical foundations.
LLM and GenAI experience is now highly valued. Add terms like 'GPT', 'LLM', 'RAG', 'fine-tuning', 'prompt engineering' to find candidates with cutting-edge skills.
Distinguish between 'Data Scientist' (modeling, statistics) and 'Data Engineer' (pipelines, infrastructure). These are different roles with different skill sets.
Skip Boolean Search Entirely
Recruiter Copilot uses AI to match candidates against your job description automatically. No boolean strings needed - just paste a JD and let AI do the sourcing.
Add to Chrome - FreeFrequently Asked Questions
How do I find data scientists with LLM experience?
Add GenAI-specific terms: AND ("LLM" OR "large language model" OR "GPT" OR "transformer" OR "RAG" OR "fine-tuning" OR "prompt engineering"). This is a rapidly evolving field, so also search for specific model names and frameworks like 'LangChain' or 'Hugging Face'.
Should I search for 'Data Scientist' or 'ML Engineer'?
They overlap but differ. Data Scientists focus on analysis, experimentation, and modeling. ML Engineers focus on productionizing models, building pipelines, and MLOps. Include both in your search, then filter based on the specific role requirements.
How do I find data scientists with PhD backgrounds?
Add education signals: AND ("PhD" OR "Ph.D." OR "Doctor of Philosophy" OR "postdoc" OR "research scientist"). You can also search for specific university names or 'published' and 'paper' to find candidates with academic research backgrounds.
What signals indicate a senior data scientist on LinkedIn?
Look for: production ML deployment experience (not just notebooks), mentions of A/B testing at scale, team leadership or mentoring, cross-functional collaboration language, and specific business impact metrics. Senior DS candidates reference revenue impact, not just model accuracy.
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