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Engineering & Data

Data Scientist resume example & template

A mid-level data scientist resume from retail forecasting and healthcare claims modeling. Each bullet names the method, the data, and the decision it changed, which is what a hiring manager probes for in the first interview.

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  • Methods are named precisely (LightGBM, CUPED, difference-in-differences), so a technical reader can judge depth.
  • Models are tied to who used them and for what: pricing, safety stock, care-manager outreach.
  • Shows production and responsible-use work (retraining, drift alerts, subgroup calibration), not just notebooks.
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Daniela Ortiz
Data Scientist · Forecasting, Experimentation & Causal Inference
Minneapolis, MN(612) 555-0137daniela.ortiz@email.comlinkedin.com/in/danielaortizgithub.com/dortiz-stats

Summary

Data scientist with 7 years in retail and healthcare, working in Python and SQL. Builds demand forecasts and designs A/B tests for a national retailer, and uses quasi-experimental methods when randomization is not an option. Ships models to production with the ML platform team rather than handing off notebooks.

Experience

Data Scientist II · TargetMar 2022 – Present
Minneapolis, MN
  • Built a LightGBM demand forecast for perishable categories across 1,900 stores, lowering weekly WMAPE from 34% to 27%.
  • Designed and read 40+ A/B tests on site search ranking; added CUPED variance reduction that cut typical test length from 21 to 14 days.
  • Estimated the sales effect of a regional price change with difference-in-differences across 212 stores; finance used the estimate to set Q4 pricing.
  • Shipped the markdown model with the ML platform team as a Python package, retrained weekly in Airflow, with drift alerts in Datadog.
  • Presented quarterly model reviews to merchandising leaders, translating forecast intervals into safety-stock targets for 60 categories.
Associate Data Scientist · OptumJul 2019 – Feb 2022
Eden Prairie, MN
  • Trained an XGBoost 30-day readmission model on 1.2M claims; care managers used its top-decile list to prioritize outreach calls.
  • Cleaned and joined claims, pharmacy and eligibility tables in Snowflake into a member-month feature set reused by 3 teams.
  • Wrote SHAP-based reason codes so nurse care managers could see why each member was flagged before calling.
  • Audited model calibration by age band and sex before launch and documented the results for the compliance review.

Education

M.S. Statistics · University of MinnesotaMay 2019
B.A. Economics, minor in Mathematics · Macalester CollegeMay 2017

Skills

Languages: Python (pandas, scikit-learn, statsmodels), SQL, R
Methods: Time-series forecasting, Gradient boosting, A/B testing and CUPED, Difference-in-differences, Propensity score matching, Model explainability (SHAP)
Platforms: Snowflake, Databricks, Airflow, MLflow, Git, Tableau

How to write a data scientist resume

What hiring teams in this field actually screen for, and the terms that get matched.

What data science hiring managers screen for

Hiring managers want to know which kind of data scientist you are before they read anything else: analytics and experimentation, classical statistics and causal inference, production machine learning, or applied LLM work. Make your headline and first bullets answer that. Then show that a model changed a decision. A forecast is a weak claim until you say who used it and what they did differently, such as setting safety stock or prioritizing outreach. Expect every bullet to be questioned in the interview, so only list methods you can defend when someone pushes back on your choices.

Methods and tools that get matched

Most postings list SQL and Python as requirements, and many still mention R. Beyond the languages, name methods the way the posting does: A/B testing, experimentation, causal inference, difference-in-differences, propensity score matching, time-series forecasting, gradient boosting, and model monitoring. Name the platforms you worked in (Snowflake, Databricks, Airflow, MLflow) because teams filter on stack. Report model quality in the metric your field uses, such as WMAPE for forecasts or AUC and calibration for risk scores, rather than a bare accuracy figure.

Common mistakes on data scientist resumes

The most common one is a list of Kaggle projects and course certificates with no shipped work; screeners discount side projects that never met real data or real users. Another is overstating machine learning for a role that is mostly analytics, which falls apart in the technical screen. Avoid accuracy numbers with no baseline and no business outcome. Leave out every library you have ever imported; a short, honest stack reads better. Finally, if your title hid the work (analyst, research associate), let the bullets make clear what you actually modeled.

Data Scientist resume FAQ

Quick answers before you start writing.

What should a data scientist resume include?

A strong data scientist resume opens with a concise professional summary, then work experience written as quantified, results-first bullets, followed by education, a skills section, and any certifications. The example above shows each section in order.

What skills should a data scientist resume highlight?

Lead with the skills the job posting asks for. For a data scientist, recruiters and ATS filters commonly look for Python (pandas, scikit-learn, statsmodels), SQL, R, Time-series forecasting, Gradient boosting, and A/B testing and CUPED. Group them so they are easy to scan.

Is this data scientist resume template ATS-friendly?

Yes. It uses a single-column structure, standard section headings, real text (no text trapped in images), and no tables or graphics that confuse applicant-tracking systems, so it parses cleanly while still looking polished.

How long should a data scientist resume be?

One page is ideal for most data scientists. Use two pages only if you have ten or more years of directly relevant experience, then tune the text size and margins so it stays clean.

More resume templates

Different role? Start from one of these, or browse every role in the Classic style.

Writing the cover letter too? See the Data Scientist cover letter example.

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