Data Scientist resume
The bar here is deployment. A resume full of notebooks that never left a laptop reads very differently from one where a model went into production and someone acted on its output.
- 01Whether a model of yours reached production, and what it was worth once there.
- 02Framework overlap with the posting. scikit-learn, PyTorch and TensorFlow aren't interchangeable on a keyword screen, whatever their conceptual overlap.
- 03Model performance stated using the metric that actually matters for that problem, beyond plain accuracy.
- 04Comfort with the whole data pipeline, all the way to the modelling step.
Modelling
- scikit-learn
- PyTorch
- TensorFlow
- XGBoost
- NLP
- time series
Engineering
- Python
- SQL
- Spark
- Airflow
- MLflow
- feature engineering
Deployment
- model deployment
- AWS SageMaker
- Docker
- A/B testing
- model monitoring
Put down only what is true and what you can be interviewed on. A term you cannot defend will win you the screening and then lose you the interview.
Built a machine learning model to predict customer churn with 87% accuracy.
Shipped a churn model (0.81 AUC, 87% precision at the intervention threshold) into the CRM; the retention team's targeted outreach cut monthly churn from 4.2% to 3.1% over two quarters.
- Quoting accuracy on an imbalanced dataset. Any interviewer will ask about class balance, and a 97% accuracy on a 3% positive rate is a red flag.
- Listing Kaggle competitions above work projects. Fine as supporting evidence, weak as the headline.
- No mention of how the model was served or monitored, which is most of the job after month one.
Check yours against a real posting
Paste your resume and a data scientist job description into the free ATS score checker or browse live data scientist openings.
Check My ATS Score FreeHow do I move from data analyst to data scientist on paper?
Lead with anything predictive or experimental you have done, put SQL and BI work below it, and make sure at least one project shows a model in use rather than in a notebook.
Should I list every algorithm I know?
No. List the families you can be interrogated on and let the projects show the rest.
Do research papers help?
For research-leaning roles, considerably. For applied product roles, a deployed model matters more.