Data Scientist Resume: Free Template & Example 2026

A data-driven resume showcasing machine learning expertise, statistical modeling, and high-impact analytics projects at leading tech companies.

Thomas Weber

Senior Data Scientist

Contact

thomas.weber@email.com

+49 176 555 0247

Berlin, Germany

linkedin.com/in/thomasweber

Skills

Python / R

100%

Machine Learning

100%

Deep Learning (PyTorch)

80%

SQL / Spark

80%

Statistical Modeling

100%

Languages

German

Native

English

C2

Interests

Kaggle CompetitionsPianoHiking

Profile

Data scientist with 5 years of experience in machine learning and predictive analytics. PhD in Statistics with a focus on Bayesian inference and causal modeling applied to product growth.

Experience

Senior Data Scientist2022 - Present

Netflix · Berlin, Germany

•Built recommendation engine improving user engagement by 23%

•Developed A/B testing framework adopted across 40+ product teams

•Published 2 papers on causal inference methods at NeurIPS

Data Scientist2020 - 2022

Spotify · Stockholm, Sweden

•Created ML models powering music discovery features for 400M+ users

•Optimized ad targeting algorithms increasing click-through rate by 45%

Education

PhD Statistics2020

ETH Zurich

BSc Mathematics2016

TU Munich

Projects

PredictHealth2023

Open-source ML model for early disease detection — 94% accuracy on benchmark

Certifications

TensorFlow Developer Certificate2021

Google

Create your Data Scientist Resume

Key Skills for a Data Scientist Resume

A compelling data scientist resume demonstrates analytical depth and practical ML expertise. Include Python, R, SQL, ML frameworks (TensorFlow, PyTorch, scikit-learn), and data tools (Spark, Hadoop, Airflow). Highlight statistical methods, experiment design, and data visualization. Domain knowledge in the target industry strengthens your application.

Tips for Your Data Scientist Resume

Lead with business impact: revenue increases, cost savings, or efficiency gains from your models. Describe model performance with relevant metrics. Include both academic research and industry applications. Link to your GitHub, Kaggle profile, or published papers.

Sections to Highlight

Experience should detail datasets, methodologies, and business outcomes. Education is important. A Publications section adds academic credibility. Skills: languages, frameworks, cloud platforms. Projects and competitions demonstrate practical ability.