Data Scientist

Ebiquity Open · verified Oct 24, 2026

Remote Spain Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at Ebiquity. Remote, Spain · full-time.

Pay not stated Data Scientist salary

RoleData Science

SeniorityMid-level

LocationSpain

WorkplaceRemote

EmploymentFull-time

PostedSep 23, 2026 · 4w ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Clean and check client datasets with SQL and Python or R before using them in analysis
Build and assess regression, machine-learning and forecasting models using sound statistical methods
Turn repeat analyses into pipelines, functions and tools the team can use again
Use Git to contribute to the shared codebase and document work so others can review and rerun it

What you bring

One to two years working in analytics or data science
A degree in a quantitative subject such as computer science, statistics or economics
Strong Python or R skills, SQL, and grounding in regression, machine learning and model validation
Working knowledge of Bayesian methods and comfort using Git
Fluent written and spoken English

Who this fits

This hands-on role suits someone who enjoys modelling and engineering, and can work independently on clearly scoped problems. You must be based in Spain.

From the employer

Location: Spain

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.

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

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