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Data Scientist resume example

Hiring managers for data science want proof that your models reached production and moved a metric. Show the problem, the method and the business result, and keep the tools list honest — depth beats a long list.

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Key skills for a data scientist resume

  • Python (scikit-learn, PyTorch)
  • Statistics and experimentation
  • Feature engineering
  • SQL and data pipelines
  • MLOps (MLflow, Docker)
  • Communicating results to non-experts

Daniel Okafor

Data Scientist

Summary

Data scientist with 5 years of experience building machine learning models that run in production. Shipped a fraud model that cut losses by £3M a year and a recommendation system that grew basket size by 8%. Experienced with Python, PyTorch, SQL and MLOps, and skilled at explaining results to executives.

Experience

Data ScientistFeb 2021 – Present
Monzo
  • Built and deployed a gradient-boosted fraud model (AUC 0.93), reducing fraud losses by £3M a year
  • Designed 25 A/B experiments with a Bayesian framework now standard across the company
  • Cut model retraining time from 6 hours to 40 minutes by moving pipelines to MLflow and Spark
Machine Learning EngineerSep 2018 – Jan 2021
Ocado
  • Launched a product recommendation model that increased average basket size by 8%
  • Reduced demand-forecast error by 22% using gradient boosting and weather features
  • Mentored 3 graduate data scientists through their first production models

Education

MSc Machine Learning2017 – 2018
University College London
BSc Mathematics2014 – 2017
University of Manchester

How to write a data scientist resume

  1. Write "deployed" or "in production" when true — it separates you from notebook-only candidates.
  2. Give model metrics with business context: "AUC 0.91, reducing fraud losses by $3M".
  3. Put publications or Kaggle results under Key achievements, not in the summary.

ATS keywords for data scientist jobs

Applicant tracking systems rank resumes by how well they match the job post. Use the keywords that appear in the posting you are applying for — these are the most common:

  • machine learning
  • Python
  • deep learning
  • NLP
  • statistics
  • model deployment
  • feature engineering
  • SQL
  • experimentation
  • MLOps

Not sure your resume passes? Run it through the free ATS resume checker, or start from one of the free templates.

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