Data Scientist & ML Engineer Resume: 55+ ATS Keywords by Specialty

Data Science and ML Engineer postings are keyword-dense — and increasingly specific about which flavor of ML you actually do. A resume that just says "machine learning" and "Python" is leaving most of the keyword-match score (25% of your total) on the table. Here's the breakdown by specialty.

Classical data science / analytics

Python, R, SQL, pandas, NumPy, scikit-learn, statistical modeling, hypothesis testing, A/B testing, regression, classification, feature engineering, data visualization, Tableau, Looker, exploratory data analysis (EDA), experiment design.

Deep learning / ML engineering

PyTorch, TensorFlow, neural networks, CNNs, transformers, model training, hyperparameter tuning, model evaluation, cross-validation, computer vision, NLP, GPU training, distributed training.

LLM / applied AI (fast-growing category)

Large language models (LLMs), prompt engineering, fine-tuning, RAG (retrieval-augmented generation), embeddings, vector databases (Pinecone, Weaviate, FAISS), LangChain, OpenAI API, Anthropic API, evaluation harnesses, hallucination mitigation.

MLOps / production ML

Model deployment, MLflow, Kubeflow, model monitoring, feature stores, CI/CD for ML, Docker, Kubernetes, Airflow, data pipelines, model drift, A/B testing in production, SageMaker, Vertex AI.

Data engineering adjacency (often required even for DS roles)

ETL/ELT, Spark, Kafka, dbt, Snowflake, BigQuery, Redshift, data warehousing, batch and streaming pipelines.

Quantify like a scientist, not a job description

Weak: "Built machine learning models to improve recommendations." Strong: "Built a gradient-boosted recommendation model that lifted click-through rate 14% across 3M weekly users, reducing inference latency 30% via feature caching." Numbers on accuracy, latency, scale, and business impact all match separately — stack them.

Don't bury your stack in a skills list only

Many ATS platforms weight keywords found in work-experience bullets higher than a bare skills list at the bottom. Mention your core tools inside at least one achievement bullet per role, not just in a "Skills: Python, PyTorch, SQL" line.

Check your match in 20 seconds

Paste your resume and a real job posting into our free scanner — it flags exactly which ML/DS keywords that JD expects and you're missing, no signup required for the first scan. Try it at /app.

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