Ebiquity

Independent authority in Marketing Effectiveness analytics

Data Scientist

Data ScienceUpdated on Nov 13

Full-timeSofia, BulgariaNo salary listedHybrid

About the Job

Requirements

1–2 years of experience in an Analytics or Data Science team.
A degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or a related quantitative field.
Strong coding skills in Python or R; experience with both is a plus.
Proficiency in SQL.
Solid statistics knowledge, including regression, machine learning fundamentals, and model validation.
A working understanding of Bayesian methodologies.
Comfort working with Git.
Fluency in written and spoken English.

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 statistical reasoning, including a working understanding of Bayesian concepts such as priors, uncertainty, and posterior interpretation.
Automate recurring analysis by creating reusable 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.

Desired Qualifications

Hands-on experience with Bayesian tools such as Stan, PyMC, brms, or similar.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience in media, marketing, or marketing-effectiveness work.
Experience with time series, causal inference, or test design.

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

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

About the Company

Ebiquity

Independent authority in Marketing Effectiveness analytics

Ebiquity serves as an independent authority in Marketing Effectiveness, helping the world’s leading advertisers improve how they buy and measure media through data-backed insights and impartial advice. It analyzes more than $100 billion in annual media spend with a network of 650 experts across 19 countries, turning data into governance and strategy to guide investment decisions. The company differentiates itself by being an impartial adviser with global reach and deep local market knowledge, not a media-buying platform or vendor. Its goal is to enable effective and responsible advertising by delivering actionable insights, strong governance, and measurable ROI improvements.

Company size: 501-1,000
Company stage: Not listed
Total funding: Not listed
Headquarters: London, United Kingdom
Founded: 1997

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