Data Scientist resume example

Data science resumes are judged on whether a model actually changed a business number, not on the sophistication of the algorithm. State the model type and the metric it moved — churn reduction, revenue lift, forecast accuracy — and be specific about the experiment design behind the claim.

Recruiters also check for statistical rigor: mention the testing method (A/B, causal inference) so it's clear the result wasn't just correlation dressed up as insight.

Elena Petrova

Data Scientist

Boston, MA elena.petrova@email.com +1 (617) 555-0161 linkedin.com/in/elenapetrova github.com/epetrova-ds

Summary

Senior Data Scientist with 6+ years of experience developing machine learning models and predictive analytics systems in Python, SQL, and AWS. Proven track record of translating complex business problems into high-impact statistical solutions, boosting customer retention by 19% and driving over $2.4M in incremental revenue through algorithmic personalization.

Experience

Senior Data Scientist

Harborlight Analytics · Boston, MA

May 2022 — Present

Built an XGBoost churn-prediction model on 2m user records, identifying at-risk accounts with 84% precision and lifting retention by 19%.
Engineered a real-time recommendation engine in Python and Redis, lifting average order value by 14% across 450k active shoppers.
Designed statistical A/B testing frameworks across 20 product experiments, reducing required sample duration from 4 weeks to 9 days.

Data Scientist

Quinvera Health · Boston, MA

Jan 2019 — Apr 2022

Automated ETL pipelines in PySpark and Snowflake, cutting daily feature generation runtime from 5 hours to 35 minutes.
Delivered executive churn dashboards in Tableau and Streamlit, enabling weekly retention interventions for 50 account executives over 12 months.
Mentored 4 junior analysts on statistical modeling and SQL optimization, improving team query performance by 40% over 12 months.

Skills

Python · SQL · pandas · scikit-learn · XGBoost · A/B Testing · Statistical Modeling · Tableau · Jupyter · Spark · Predictive Modeling

Education

Boston University

M.S. Statistics

2017 — 2019

Boston University

B.A. Mathematics

2013 — 2017

Data Scientist · Modern Sidebar template · single-column, ATS-safe.

ATS keywords for a Data Scientist resume

Applicant tracking systems match your resume against the job description's vocabulary. Mirror the terms below that are true of you — ideally with a metric attached.

PythonRpandasNumPyscikit-learnSQLXGBoostA/B TestingStatistical ModelingHypothesis TestingTableauJupyterFeature EngineeringCausal InferenceApache Spark

What recruiters look for

A model or analysis tied to a specific business metric it improved, with a number attached.
Statistical method named explicitly — A/B testing, regression, causal inference — not just 'analyzed data'.
SQL and a programming language (Python or R) both present, since most roles require both.
Evidence of communicating findings to non-technical stakeholders, not just building models in isolation.
Production or deployment experience if the role isn't purely research (model serving, monitoring drift).

Before & after: one bullet

Weak

Built machine learning models to predict customer churn.

Strong

Built an XGBoost churn model (AUC 0.87) that flagged at-risk accounts 3 weeks earlier, cutting quarterly churn 9% after retention-team rollout.

Common mistakes to avoid

Describing models built with no mention of the metric or dollar impact they produced.
Overloading the resume with academic publications when the role is applied, industry-facing work.
No SQL mentioned, which is a near-universal requirement recruiters filter on first.
Vague 'used machine learning' language instead of naming the specific algorithm or library.