Data Scientist

tails.com

. Own Tails.com's predictive modelling and machine learning work, focusing on improving customer lifetime value and sustainable, profitable growth .

Posted 11/9/2026full-timeRichmond • United KingdomJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in predictive modeling and machine learning to enhance customer lifetime value and drive sustainable growth. Proficient in deploying statistical models and leveraging data science insights to optimize marketing strategies and customer retention.

Highest-signal resume keywords

Predictive ModelingMachine LearningCustomer Lifetime Value ModelingExperimental DesignPython and SQL Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingChurn ModelingSurvival ModelingPropensity ModelingA/B TestingIncrementality MeasurementMarketing Mix ModelingData Science LibrariesData Pipeline DevelopmentCloud Platforms

Soft Skills

Decision-MakingStakeholder ManagementCollaboration

Tools & Technologies

AWSAirflowDagsterSnowflake ML

Industry Keywords

Subscription BusinessD2C BusinessCustomer ExperienceCRMPerformance Marketing

Tech Stack

Tools & technologies

AirflowAWSCloudPandasPythonScikit-LearnSnowflakeSQL

About the role

Key responsibilities & impact

Own Tails.com's predictive modelling and machine learning work, focusing on improving customer lifetime value and sustainable, profitable growth
Build and develop models to identify customers likely to stay, spend and engage long-term
Use data science insights to improve acquisition strategies, customer retention and the customer experience
Work with Performance Marketing, CRM, Customer Experience & Retention, Product, Finance, Engineering and Data teams
Own projects from opportunity identification and model building through testing, implementation and measuring commercial impact
Build relationships with key stakeholders and understand the customer lifecycle, data infrastructure, existing models and commercial priorities
Own the lifetime value modelling roadmap and improve existing predictions
Predict each new customer's lifetime value after sign-up using acquisition source, behaviour, dog and plan data, and early engagement
Send predictions to acquisition partners such as Meta and Google and ensure events are complete, timely and correctly matched
Compare channels by customer value rather than only cost per sign-up
Help build marketing mix modelling to show how channel spend drives valuable customers
Identify and test changes that improve trial-to-paid conversion
Determine which new customers need additional early-life support and match interventions to risk and value
Run controlled tests with CRM and Customer Experience & Retention
Establish minimum testing and holdout standards
Deploy models to production with data engineering support and monitor health, drift and retraining

Requirements

What you’ll need

2-4+ years in a data science role, with a proven track record of deploying statistical and machine learning models on complex, messy, real-world data, and showing the business impact they had
Experience building customer lifetime value, survival, propensity or churn models, ideally for a subscription business and used to drive CRM or marketing activity
Strong experimental design and causal inference: A/B tests, holdouts and control groups, uplift measurement and incrementality
Experience feeding model outputs into paid media, such as value-based bidding, offline or server-side conversion events, or predicted-value audiences on Meta or Google
Experience with marketing mix modelling or attribution
A bachelor's or master's degree in a STEM related field
Advanced proficiency in Python and SQL with extensive experience working with core data science libraries (e.g. pandas/polars, scikit-learn)
Familiar with cloud platforms (e.g. AWS) and orchestration tools (e.g. Airflow, Dagster) in relation to operationalising data science products
Experience leveraging Snowflake ML and robust data pipelines to deliver scalable, production-ready data science solutions
A decision-first mindset: you start from the business decision and its owner, and you're comfortable recommending to stop when a test doesn't deliver
Subscriptions or D2C business experience (highly desirable)

Benefits

Comp & perks

Private Healthcare through AXA
A 9 day fortnight - our office is closed every other Friday!
25 days of Annual Leave and 8 additional remote working days