Data Scientist - Partnerships Strategy

iwoca
London£60k – £90kPosted 30 March 2026

Job Description

Data Scientist - Partnerships Strategy DATA SCIENTIST - PARTNERSHIPS STRATEGY Hybrid in London, UK We’re looking for a Data Scientist to join our Partnerships Strategy team You’ll shape how iwoca works with partners by influencing pricing, commission, and engagement decisions that drive more than half of our new customer acquisition. The company Small businesses move fast. Opportunities often don’t wait, and cash flow pressures can appear overnight. To keep going, and growing, SMEs need finance that’s as flexible and responsive as they are. That's why we built iwoca. Our smart technology, data science and five-star customer service ensures business owners can act with the speed, confidence and control they need, exactly when it's needed. We’ve already cleared the way for 100,000 businesses with more than £4 billion in funding. Our passionate team is driven to help even more SMEs succeed, through access to better finance and other services that make running a business easier. Our ultimate mission is to support one million SMEs in their defining moments, creating lasting impact for the communities and economies they drive. The team The Partnerships Strategy team supports iwoca’s commercial teams by turning partner performance and behaviour into clear, data-led guidance. The team analyses experiments and builds models to understand how pricing, commission structures, and partner engagement affect customer acquisition and profitability. The team is small and interdisciplinary, combining commercial strategy, business analysis, and data science. It works closely with partner-facing teams to translate business questions into quantitative problems and to present evidence in a way that supports sound, timely decisions. The role iwoca's Data Scientists specialise in supervised machine learning, statistical inference and exploratory data analysis, focusing on tabular and time-series data. Their work emphasises quantitative predictions through the analysis of conditional probabilities and expectations, using medium-sized datasets. Working in the Partnerships Strategy team, you’ll model customer price sensitivity to support pricing strategy, analyse differences in how partners operate to guide commercial treatment, and evaluate how relationship management effort translates into performance and profitability. You’ll work closely with commercial and strategy colleagues and see your analysis applied directly in day-to-day decisions. The requirements Essential: - Expertise in probability and statistics, gained through work in a quantitative field such as Mathematics, Statistics, Physics, Engineering, or similar. - Ability to understand business context and translate data into actionable insights that guide decisions. - Proficiency with data manipulation and modelling tools such as pandas, statsmodels, or R. - Experience with scientific computing tools such as NumPy or SciPy. - Ability to work autonomously and manage analytical work from framing the question through to making a recommendation. - Ability to communicate clearly in writing and speech, adapting technical detail to different audiences. - A commitment to using modern tools effectively – including AI – to maximise quality, speed, and rigour, while retaining responsibility for accuracy and outcomes. Bonus: - Understanding of Bayesian statistics, including interest in or experience with hierarchical models. - Experience building or adapting statistical or machine-learning models, with an interest in understanding the underlying methods. - Familiarity with stochastic modelling concepts as they apply to inference, time series, or uncertainty. - Understanding of financial concepts such as pricing or deterministic cash flows. The salary We expect to pay from £60,000 - £90,000 for this role, depending on experience. But, we’re open-minded, so definitely include your salary goals with your application. We routinely benchmark salaries against market rates, and run ... (truncated, view full listing at source)
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