# Data Scientist résumé example

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

![Data Scientist résumé example — senior, written for United States, set in the Marker design](https://cvaurum.com/img/examples/data-scientist.webp)

- Field: Data & Analytics
- Career stage: Senior
- Written for: United States
- Design: Marker (https://cvaurum.com/templates/marker)
- Open it: https://cvaurum.com/examples/data-scientist

Every name, employer, address, phone number and figure below is invented.

---

## Naomi Adeyemi — Senior Data Scientist

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.

### 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