Own data science initiatives across forecasting, classification, experimentation, recommendation, ranking, segmentation, and pricing. Develop and deploy predictive and econometric models for B2B buyer behavior and wholesale market dynamics. Design A/B tests, apply causal inference and regression techniques, collaborate with engineering on MLOps workflows, and communicate analytical recommendations and model limitations to Product, Finance, and Commercial stakeholders.
You're a data scientist with broad quantitative skills and a background in microeconomics, econometrics, or finance. You'll own data science work across Qogita's business — from forecasting and classification through to experimentation and recommendation systems — and act as the team's go-to on how prices are set, how buyers respond, and how market structure shapes commercial decisions. The Data Science team works cross-functionally with Product, Finance, and Commercial teams to build the analytical and modelling layer that drives Qogita's wholesale marketplace.
What you'll do
What you'll bring
Benefits
Qogita [Ko-gi-ta] is on a mission to make global trade radically efficient by building the operating system for modern wholesale.
Wholesale is a €50 trillion market still largely run through phone calls, catalogues and trade shows. Behind every product sits a fragmented chain of sourcing, trading and logistics that makes wholesale slower, more complex and expensive than it should be.
Qogita is changing this by connecting the global market into a single order book, building the rails to move products across borders efficiently, and providing the intelligence to help businesses know what to stock, what it’s worth and where it should go.
We operate across health and beauty in 30+ European markets, with ambitions to reach every category, everywhere. Backed by Accel, Bessemer, Dawn and LocalGlobe, we’re one of Europe’s fastest-growing B2B companies.
We’re an ambitious, pragmatic and highly collaborative team, united by a desire to reshape one of the world’s biggest markets.
What you'll do
- Build and deliver data science solutions across the stack — predictive models, segmentation, forecasting, ranking systems, and pricing models — depending on where the business need is greatest
- Act as the team's domain expert on pricing and market economics: take ownership of the modelling approach, analytical strategy, and how findings translate into commercial recommendations
- Research, build, deploy and maintain predictive and analytical models that reflect B2B buyer behaviour and wholesale market dynamics
- Design and analyse experiments and A/B tests, owning statistical validity and translating results into recommendations Product and Commercial can act on
- Apply a range of quantitative methods — regression modelling, causal inference, ML techniques — to business problems across pricing, demand, market liquidity and beyond
- Collaborate with Engineers to ship models via reproducible MLOps workflows, including experiment tracking, model serving, and production monitoring
- Communicate findings and model limitations clearly to Finance, Commercial, and Product stakeholders
What you'll bring
- 3+ years working as a data scientist or quantitative analyst and meaningful exposure across ML methods and statistical modelling with a focus on microeconomics, econometrics or finance
- Strong Python (pandas, statsmodels, scikit-learn, XGBoost, PyTorch) and SQL; comfortable working with large transactional datasets
- Grounding in pricing and market economics — price theory, consumer behaviour, substitution effects, and how market structure shapes pricing power
- Familiarity with econometric techniques for demand estimation, forecasting and measuring causal effects
- Experience designing and analysing experiments with real business decisions riding on the results
- Able to communicate findings and model limitations clearly to non-technical stakeholders across Finance, Commercial, and Product
- Bachelor's or Master's in Data Science, Statistics, Economics, Econometrics, Mathematics, or a related quantitative field
Benefits
- Base salary: €60,000 – €75,000 (Amsterdam) / £72,000 – £90,000 (London) depending on experience
- 26 days of annual leave, plus 4 additional personal days
- Company performance-based bonus
- Attractive equity package
- Pension contributions
- Annual learning & development budget
- Office-led culture with hybrid flexibility
- Dog-friendly offices
- Home-office setup package
- Office socials and annual company-wide offsite
Qogita [Ko-gi-ta] is on a mission to make global trade radically efficient by building the operating system for modern wholesale.
Wholesale is a €50 trillion market still largely run through phone calls, catalogues and trade shows. Behind every product sits a fragmented chain of sourcing, trading and logistics that makes wholesale slower, more complex and expensive than it should be.
Qogita is changing this by connecting the global market into a single order book, building the rails to move products across borders efficiently, and providing the intelligence to help businesses know what to stock, what it’s worth and where it should go.
We operate across health and beauty in 30+ European markets, with ambitions to reach every category, everywhere. Backed by Accel, Bessemer, Dawn and LocalGlobe, we’re one of Europe’s fastest-growing B2B companies.
We’re an ambitious, pragmatic and highly collaborative team, united by a desire to reshape one of the world’s biggest markets.
Qogita London, England Office
1 Poultry, London, United Kingdom, EC2R 8AJ
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