You will join our Data Science team and help turn client data into reliable models and reusable analytics tooling. This is a hands-on modelling and engineering role: you will spend your time on data, code, and statistical methods.

Key Responsibilities

- Prepare, clean, and quality-check datasets using SQL and Python or R

- Build and validate statistical models, including regression, machine learning, and forecasting

- Apply sound statistical thinking, including a working understanding of Bayesian ideas (priors, uncertainty, posterior interpretation)

- Automate recurring analysis so the team can reuse pipelines, functions, and tools

- Use Git to work with the team’s codebase

- Document methods and results clearly so others can review, rerun, and present the work

Skills, Knowledge and Expertise

- 1–2 years in an Analytics or Data Science team

- Degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or a related quantitative field





- Strong coding in Python or R (both is a plus)

- SQL

- Solid statistics: regression, machine learning fundamentals, and model validation

- Working understanding of Bayesian methodologies

- Comfortable with Git

- Fluent English, written and spoken

- Intellectually curious, organised, and able to work independently on well-scoped problems

Nice to have

- Hands-on Bayesian tooling (Stan, PyMC, brms, or similar)

- Cloud familiarity (AWS, Azure, or GCP)

- Experience in media, marketing, or marketing-effectiveness work

- Time series, causal inference, or test design

Benefits

What we can offer:

- Competitive salary

- Training and Development Opportunities

- Summer schedule July - Sept

- 6 hour work day on Fridays (9.00 – 15.00)

- Birthday day off

📌 Data Scientist (España)
🏢 Ebiquity
📍 España