Data Science Resume Keywords for ATS (2026)

Add data science resume keywords for machine learning, experimentation, data engineering, analytics, AI, and model impact.

Quick answer: feature Python, SQL, ML libraries (Scikit-learn, PyTorch, TensorFlow), experimentation, and model-evaluation language from the job description. Truthfully add LLM, RAG, or embeddings terms only when you have shipped work, and prove every claim with metrics like AUC, lift, or business impact.

Core data science resume keywords

Machine LearningStatistical ModelingA/B TestingForecastingExperimentationData EngineeringModel EvaluationPredictive AnalyticsNLPGenerative AI

Tools and platforms ATS systems can match

Python

SQL

Pandas

Scikit-learn

TensorFlow

PyTorch

Spark

Airflow

Databricks

Tableau

Action verbs for data science resumes

ModeledPredictedSegmentedEvaluatedAutomatedForecastedExperimentedDeployed

Natural keyword phrases

These phrases show keywords in context. Use them as structure, then replace the details with your actual work.

Built churn prediction model for retention outreach

Designed A/B test analysis for product decisions

Automated data pipeline for model training

Evaluated model performance and business impact

Keyword-rich bullet examples

Built churn prediction model with 0.84 ROC-AUC, helping retention team prioritize 18K at-risk accounts.

Designed A/B test analysis for onboarding flow, identifying variant that lifted activation by 11%.

FAQ

What are strong data science resume keywords?

Use Python, SQL, machine learning, statistics, experimentation, model evaluation, data pipelines, visualization, and domain-specific AI terms from the role.

Should I include AI keywords?

Yes when truthful. Add terms like NLP, LLM, RAG, embeddings, model evaluation, or generative AI only when you have relevant projects or work experience.

Related industries

Roles often borrow keywords across adjacent fields. Browse a related industry to find overlap with your background.

Tech Resume Keywords

Use the right software, product, cloud, data, and engineering keywords without stuffing your tech resume.

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Engineering Resume Keywords

Use engineering resume keywords for design, testing, manufacturing, quality, CAD, process improvement, and compliance.

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Finance Resume Keywords

Target finance roles with keywords for FP&A, accounting, reporting, compliance, modeling, and business analysis.

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Core data science resume keywords

Machine LearningStatistical ModelingA/B TestingForecastingExperimentationData EngineeringModel EvaluationPredictive AnalyticsNLPGenerative AI

Tools and platforms ATS systems can match

Python

SQL

Pandas

Scikit-learn

TensorFlow

PyTorch

Spark

Airflow

Databricks

Tableau

Action verbs for data science resumes

ModeledPredictedSegmentedEvaluatedAutomatedForecastedExperimentedDeployed

Natural keyword phrases

These phrases show keywords in context. Use them as structure, then replace the details with your actual work.

Built churn prediction model for retention outreach

Designed A/B test analysis for product decisions

Automated data pipeline for model training

Evaluated model performance and business impact

Keyword-rich bullet examples

Built churn prediction model with 0.84 ROC-AUC, helping retention team prioritize 18K at-risk accounts.

Designed A/B test analysis for onboarding flow, identifying variant that lifted activation by 11%.

FAQ

What are strong data science resume keywords?

Use Python, SQL, machine learning, statistics, experimentation, model evaluation, data pipelines, visualization, and domain-specific AI terms from the role.

Should I include AI keywords?

Yes when truthful. Add terms like NLP, LLM, RAG, embeddings, model evaluation, or generative AI only when you have relevant projects or work experience.

Related industries

Roles often borrow keywords across adjacent fields. Browse a related industry to find overlap with your background.