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.
Key Responsibilities
- 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.
Essential Skills & Knowledge
- 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 Skills & Knowledge
- 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.
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