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Data Scientist résumé example

Data Scientist résumé example — senior, written for United States, set in the Marker design
Data Scientist résumé example, in the Marker design

A senior data scientist returning from a planned career break, with the gap stated plainly and the best work after it.

Written for United States, at senior, in the data & analytics field, shown in the Marker design. Every name, employer, address and number below is invented.

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Naomi Adeyemi — Senior Data Scientist

Boston, MA

Data scientist with eleven years in healthcare and energy, working mostly on forecasts and risk models other teams depend on daily. Took a utility's day-ahead load forecast from 4.8% to 2.9% mean absolute percentage error, worth roughly $6.1m a year in avoided imbalance charges. Returned from a planned career break in 2023 and now sets the review standard for models that touch billing.

Experience

Senior Data Scientist, Granite Harbor Power · September 2023 – present

Forecasting and asset-risk group of eight. Returned at three days a week and moved to full time in March 2024.

  • Owns the day-ahead load forecast for 2.4 million meters; mean absolute percentage error fell from 4.8% to 2.9%, about $6.1m a year in avoided imbalance charges.
  • Built the outage-risk model that ranks 41,000 distribution poles for inspection; crews now find a defect on one visit in three rather than one in eleven.
  • Set the review standard for any model that touches billing: written assumptions, a fixed backtest window, and a named owner. Eight models cleared it in the first year.
  • Rewrote the forecast backtest to respect the data available at prediction time, which revealed that two years of reported accuracy had been optimistic by 0.6 points.
  • Mentors three analysts; two have since shipped production models of their own.

Planned career break, Career break · June 2022 – August 2023

Full-time family care.

  • Completed Harvard Extension School coursework in causal inference and shipped two releases of an open-source forecasting package.

Data Scientist, Alderbrook Health Analytics · March 2018 – May 2022

  • Built the readmission risk model used across nine hospitals; 30-day readmissions in the flagged cohort fell 18% once care management began working its daily list.
  • Replaced a purchased scoring tool with an in-house gradient-boosted model, matching its accuracy at a twelfth of the cost and making every feature auditable.
  • Ran the outreach experiment program: 31 tests in two years, four of which changed standing policy.

Analyst, then Data Scientist, Marlowe Insight Partners · July 2015 – February 2018

  • Forecast quarterly demand for 14 consumer brands, cutting overstock 27% against the planner-driven method it replaced.
  • Automated the client reporting pack, returning about 30 analyst hours a month across the team.

Projects

  • Seasoncast — An open-source seasonal forecasting package for Python, built for demand and load series with holiday effects.

Education

  • M.S. Statistics · Boston University · September 2013 – May 2015
  • B.S. Mathematics · University of Massachusetts Amherst · September 2009 – May 2013

Skills

  • Modeling: Time series forecasting, Gradient boosting, Causal inference, Survival analysis, Hierarchical models
  • Tools: Python, R, SQL, PyTorch, Spark, Airflow
  • Practice: Backtesting, Model review, Experiment design, Executive briefings, Mentoring

Why this Data Scientist résumé works

  • Model accuracy is translated into money: forecast error from 4.8% to 2.9% is “about $6.1m a year in avoided imbalance charges”, which lets a non-technical reader weigh the work.
  • The career break is a dated entry with Harvard Extension School coursework and two open-source releases, and the return at three days a week is stated, so the gap is explained and then left behind.
  • Rigour is shown, not claimed: rewriting the backtest revealed two years of reported accuracy had been “optimistic by 0.6 points”. Admitting that is the senior judgement teams hire for.
  • Two publications, one on load forecasts under rooftop solar and one on scores “a care team can act on”, match the two domains on the page and back the summary’s eleven years.

Data Scientist résumé: common questions

What should a senior data scientist resume focus on?

Models in production, who depends on them, and their effect in business terms: money saved, risk reduced, decisions changed. Add the standards you set for others, such as review or backtesting rules, and mentoring results. Keep the tool list short.

How do you return to data science after a career break?

Keep skills current with a course or open-source work, and consider a part-time return if offered. On the résumé, list the break as a dated entry with what you did, then put the strongest post-return results in the summary.

How long should a data scientist resume be?

Two pages is fine with ten or more years, provided the first page carries the recent work and its results. Publications and projects can go on page two; early analyst roles need only one or two bullets.

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