Data Scientist - TH

We are looking for a Data Scientist to build our modelling and statistical capability hands-on. You will define what we model, set the technical bar for how it is done, and deliver it end to end.

This is a senior, build-from-day-one mandate where you are the technical owner of the data science work at a commercially validated, fast-growing company — shaping what gets modelled and how.

Key Responsibilities:

• The roadmap. Own the data science and modelling roadmap end to end — from the flagship Creative Intelligence Engine (CIE) build to the statistical models that power our SaaS platform.
• The flagship. Deliver CIE hands-on as your first proof point — from deconstructing video into creative signals to building statistically sound cohort benchmarks and the recommendations that follow from them.
• The bar. Set the technical standard for the function — statistical rigour, modelling discipline, and how models are validated, deployed, and trusted.
• The rigour. Bring statistical rigour to how models are built and validated. Own delivery from data layer through to reliable, deployed models.

Requirements:

• A Bachelor's degree in Statistics, Mathematics, Analytics, Economics, or another quantitative field.
• Minimum 5 years of hands-on data science experience, preferably in consumer-internet, e-commerce industries, with a track record of taking statistical models from problem definition through to validated, deployed outputs.
• Deep command of statistics and modelling — supervised and unsupervised learning, statistical inference, and regression / classification / clustering methods, with the judgment to choose the right approach for each problem.
• Significant proficiency in SQL and Python, including its statistical and data-analysis ecosystem (pandas, NumPy, scikit-learn, statsmodels).
• Clear communicator who can influence founders, product, and commercial stakeholders in a multicultural environment.

It's great if you have

• At least a MSc in Computer Science, Operations Research, Statistics, or another quantitative field.
• Experience being the first or sole data scientist on a problem, owning it end to end.
• NLP or multimodal experience across text, audio or video.
• Bayesian methods, time-series forecasting, or survival / uplift modelling.

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