Data Scientist in City of London

Location: London, UK (London)

Work pattern: Full-Time (Hybrid: minimum two days per week in our London office)

Salary: £50,000 - £65,000 per annum, DOE, generous options

Level: Mid, 2-3 years of relevant experience

Reporting line: Senior Data Scientist

Division/Team: Data Science (D&T)

Closing date: Thursday 14th May

We regret we are currently unable to provide visa sponsorship, please only apply if you have the right to work in the UK.

About Fable Data:

Fable Data is a global consumer transaction data company. We aggregate anonymised consumer data from financial services businesses, which we then enrich, productise and deliver high value data products to some of the world’s leading retailers, investment managers, technology companies, governments, and advertising firms. Our data provides a near real-time view of the consumer economy offering powerful insights into consumer behaviour, retailer performance and broader macroeconomic trends.

About the Role:

We’re looking for a talented Data Scientist ready to take the next step in their career, someone who thrives on analysing text data and is adept at using AI alongside an expansive machine learning toolkit to build high precision solutions to identify real world entities within billions of lines of text data. With access to one of the most comprehensive, market leading, multi-country consumer transaction datasets available, you will expand the merchant vocabulary (named entity recognition), build new models and enhance the accuracy of our existing models that power our world class products and the high impact insights produced by our client enablement and commercial teams.

About You:

Passionate about solving real-world problems through a blend of applied data science, analytical thinking and research. Curious with a penchant for accuracy, you love uncovering patterns in text that haven’t yet been discovered and can do so without compromising intellectual integrity and accuracy. Product driven thinking enables you to systematise your work into reusable and repeatable processes that can be integrated easily into our data platform. Thrive in a fast-paced, collaborative environment that values both analytical rigour and commercial impact.

What you’ll do:

• Contribute to the full ML lifecycle including model training, evaluation, versioning, deployment, and iterative improvement for a suite of text-based classification models.
• Assist in the development of new product concepts.
• Evaluate and validate new data sources for suitability, quality, and bias in ML training pipelines.
• Assist in developing and implementing efficient strategies for creating high-quality labelled training datasets, leveraging automation, weak supervision, and active learning techniques.
• Design, implement, and maintain rule-based data processing logic leveraging regex and other pattern-matching approaches.
• Assist in developing monitoring systems for in-life machine learning models that automatically detect and flag issues.
• Work with stakeholders to define and implement new machine learning applications based on transaction data.

Skills / knowledge:

Essential:

• 2+ years’ experience working with large datasets.
• Experience in SQL and Python in a professional context.
• Fast learner and comfortable with uncertainty and change; we are a scale-up.
• Comfortable working with data cleaning, transformation, and basic scripting tasks.
• Knowledge of or experience with developing production code and source control via Git.
• Strong attention to detail and a focus on data quality.

Desirable:

• Knowledge of or experience with Spark/Databricks.
• Experience monitoring and enhancing in-life ML Models (MLOps).
• Familiarity with classification, time series, and/or natural language processing.
• Knowledge of or experience working with consumer data, banking data, or stocks and shares.
• Planning skills to help you prioritise work across multiple projects.
• Familiarity with regex or willingness to learn quickly.

Why Fable:

At Fable, we believe in continuous improvement and shared responsibility. You’ll join a collaborative team that empowers you to take ownership of your work, experiment, and grow your skills. This is a unique opportunity to combine technical depth with commercial storytelling and have your work seen by some of the most influential organisations in the world.