Senior Data Scientist, Growth
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Before you apply
LocationLondon
Work modehybrid
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentGrowth
Company size201–500 people
First seenJul 22, 2026 · 3mo ago
Verified live7h ago
May no longer be actively hiring
First seen on the company's careers page 108 days ago42% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
5+ years in Data Science, Machine Learning, Applied Statistics, Analytics, or a related discipline
Experience building prediction models in a consumer business (B2C, D2C), ideally around LTV, growth, acquisition, retention, churn, monetisation, or customer value
Strong Python skills and experience working with large scale datasets
Solid understanding of supervised learning techniques, model evaluation, feature engineering, and statistical trade offs
Ability to translate ambiguous commercial questions into structured data science problems
Strong business judgement and the ability to connect model outputs to real decisions
Experience working cross functionally
Clear communication skills, especially when explaining modelling assumptions, limitations, and recommendations to non technical stakeholders
Comfortable operating in a fast moving environment with high ownership and evolving priorities
Fluent in English
Experience in fintech, banking, payments, investing, lending, or another financial consumer product
Experience at a high growth B2C or D2C company, such as consumer fintech, health tech, subscription, retail, wellness, or marketplace businesses
Experience with LTV, CAC, payback period, acquisition efficiency, cohort modelling, retention modelling, churn prediction, or marketing mix related problems
Experience working across multiple countries, currencies, channels, or customer segments
Experience productionising models or working closely with Engineering and Data Engineering teams to deploy data science solutions
Familiarity with MLOps, model monitoring, experiment design, causal inference, or incrementality measurement
Skills
Python
MLOps
Benefits
Stock options
Performance bonus
What We’re Looking For
We’re looking for a Senior Data Scientist to join ARQ’s Growth team as our first data science hire – owning all data science initiatives across Growth and Marketing, starting with predicting customer lifetime value across our markets and acquisition channels. You’ll report directly to the Head of Growth and our COO.
You’ll be responsible for developing, maintaining, and improving LTV prediction models across our four countries, helping us make sharper decisions on growth investment, channel performance, acquisition quality, and long term customer value.
This is a high ownership role for someone who has worked on consumer growth, LTV, acquisition, retention, or monetisation problems in a B2C or D2C environment. You should be comfortable taking ambiguous business questions, turning them into measurable modelling problems, and building solutions that influence real commercial decisions.
What You’ll Be Doing
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Design, build, maintain, and improve lifetime value prediction models across ARQ’s countries and acquisition channels.
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Work closely with Growth & Marketing, Product, Finance, Data Engineering, and Engineering teams to understand business needs and translate them into modelling solutions.
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Help evaluate acquisition quality by channel, campaign, geography, customer segment, and product behaviour.
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Build models that support better decisions around growth spend, payback periods, customer quality, retention, and long term value.
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Analyse large scale customer, product, marketing, and transaction datasets to identify patterns, risks, and opportunities.
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Continuously monitor model performance and improve accuracy, reliability, and business impact over time.
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Create clear frameworks and metrics that help teams understand the trade offs behind growth decisions.
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Partner with Data Engineering and Engineering teams to productionise models, pipelines, and reporting where needed.
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Bring a pragmatic approach to modelling, balancing technical depth with commercial impact.
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Over time, contribute to other Data Science challenges across Growth and the wider business.
What You’ll Need
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5+ years in Data Science, Machine Learning, Applied Statistics, Analytics, or a related discipline.
•
Experience building prediction models in a consumer business (B2C, D2C), ideally around LTV, growth, acquisition, retention, churn, monetisation, or customer value.
•
Strong Python skills and experience working with large scale datasets.
•
Solid understanding of supervised learning techniques, model evaluation, feature engineering, and statistical trade offs.
•
Ability to translate ambiguous commercial questions into structured data science problems.
•
Strong business judgement and the ability to connect model outputs to real decisions.
•
Experience working cross functionally.
•
Clear communication skills, especially when explaining modelling assumptions, limitations, and recommendations to non technical stakeholders.
•
Comfortable operating in a fast moving environment with high ownership and evolving priorities.
•
Fluent in English, as we collaborate with teams across the globe.
Nice To Have
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Experience in fintech, banking, payments, investing, lending, or another financial consumer product.
•
Experience at a high growth B2C or D2C company, such as consumer fintech, health tech, subscription, retail, wellness, or marketplace businesses.
•
Experience with LTV, CAC, payback period, acquisition efficiency, cohort modelling, retention modelling, churn prediction, or marketing mix related problems.
•
Experience working across multiple countries, currencies, channels, or customer segments.
•
Experience productionising models or working closely with Engineering and Data Engineering teams to deploy data science solutions.
•
Familiarity with MLOps, model monitoring, experiment design, causal inference, or incrementality measurement.
Benefits
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Competitive salary and benefits
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Stock options, so you own part of what you build
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Discretionary performance bonus
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The latest tools and technology
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A world-class team that will challenge and grow your skills
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The opportunity to help build the best fintech app in Latin America
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Office Policy: 3-4 days a week in-office