Data Scientist

Ebiquity Open · verified Oct 24, 2026

Hybrid Sofia Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at Ebiquity. Sofia · full-time.

Pay not stated Data Scientist salary

RoleData Science

SeniorityMid-level

LocationSofia

WorkplaceHybrid

EmploymentFull-time

PostedAug 21, 2026 · 2mo ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Prepare datasets with SQL and Python or R, checking their quality before analysis
Build and test regression, machine-learning and forecasting models using sound statistical methods
Automate repeated analysis into reusable pipelines, functions and tools for the team
Use Git to collaborate on code, and document methods and results so others can review and rerun the work

What you bring

You have one to two years on an analytics or data science team
A degree in a quantitative field such as computer science, statistics or economics is required
You can code in Python or R and use SQL, with a solid grasp of regression, machine learning and model validation
You understand Bayesian concepts, including priors, uncertainty and how to interpret posterior results
You are comfortable using Git and fluent in written and spoken English

Who this fits

This hands-on role suits someone who enjoys working directly with data, code and statistical methods, and can handle clearly scoped work independently. It is based in Sofia, Bulgaria, with a hybrid arrangement.

From the employer

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