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Data scientist CV example

A data scientist's CV shows models that were used: the question, the data, the method and what the business did with the answer.

Hiring managers look for the step from analysis to something running in production, and for how you explain it. This example is a data scientist four years into the work, after a maths degree and a master's.

Professional design1 page
Data scientist CV example: fictional example, page 1. Full text is available below.
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Fiona McLeod
Data Scientist
Edinburgh · 07700 900232 · fiona.mcleod@example.com · github.com/fiona-mcleod-example

Profile

Data scientist at a home energy supplier with 900,000 customers. Builds forecasting and customer models in Python, puts them into production with engineers and explains the results to people who do not work with data. Looking for a senior data scientist role.

Experience

Data Scientist, Firthside Energy, Edinburgh 2023–present

Built a half-hourly demand forecast from smart meter, weather and tariff data; forecast error fell by 18%, cutting balancing costs.

Built a model that flags customers likely to fall into debt so the support team can call them first; 2,400 were offered a payment plan early in its first winter.

Set up automated retraining and monitoring in Databricks, so models are refreshed every week without manual work.

Present results to the pricing and customer teams.

Data Analyst, Firthside Energy, Edinburgh 2022–2023

Cleaned and joined meter data and built reports in Power BI.

Education

MSc Data Science, Distinction, University of Leith 2021–2022

BSc (Hons) Mathematics, 2:1, University of Leith 2017–2021

Tools

Python (pandas, scikit-learn, LightGBM, PyTorch)

SQL, Databricks, Spark

MLflow, Git, Docker

Power BI

Skills

Forecasting and classification models

Experiment design and A/B tests

Model monitoring and data quality checks

Explaining results to non-specialists

Fictional example for a data scientist. Every person and employer in it is invented. Replace every detail with your own.

What data science teams look for, and where this CV shows it

The job asks you toWhere this CV shows it
Gather data from different sources to create models and test ideasSmart meter, weather and tariff data joined for the demand forecast
Analyse data patterns to form insights and make policy recommendationsThe early-support model and its 2,400 payment plans
Set up automated data systems to transform business processesWeekly automated retraining and monitoring in Databricks
Make sure information management meets data security and quality standardsData quality checks and model monitoring
Explain to different audiences how AI and data science can benefit their organisationPresenting results to the pricing and customer teams

The left column follows the National Careers Service job profile for a data scientist.

Facts checked against National Careers Service: Data scientist on .

Inside this example
  • Profile: 42 words here
  • Experience: 107 words here
  • Education: 20 words here
  • Tools: 17 words here
  • Skills: 23 words here

How to write yours

01

Question, method, result

Each bullet says what was asked, what you built and what changed. A model nobody used is a weaker line than a simple one that was.

02

Say it reached production

Deployment, monitoring and retraining are what separate a data scientist from an analyst on most shortlists.

03

Keep the stack honest

List libraries and platforms you have used on real work, grouped so they can be checked against the advert.

04

Show you can explain it

One line on who you present to tells a manager you can take a result to the people who act on it.

Rules and checks for a data scientist's CV

  • Routes in. Most data scientists have a degree or postgraduate qualification in maths, statistics, data science or computer science; graduates of other subjects can take a master's conversion course, and there is a Data Scientist Level 6 Degree Apprenticeship (National Careers Service).
  • Tools. The National Careers Service suggests building up coding and analysis tools such as R, SQL, Python, Power BI and Excel. Put the ones you use in their own list.
  • Personal data. Describe the data and the model, never customer records or anything your employer keeps private.

Professional and one page: the profile, results and tools are easy to find, and the layout prints cleanly for a panel interview.

Help with your next edit

CV Skills: Lists by Job and How to Prove Each One Education on a CV: UK Qualifications and Examples CV Work Experience: Turn Duties into Evidence How to Write a UK Cover Letter: Template and Example

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