Data Scientist

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