Tide is seeking a Senior Data Scientist to build robust, real-time machine learning solutions to combat financial crime, with a focus on driving impact by optimising costs and reducing risk using ML/Stats models.

Requirements

4+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).

Experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment.
AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
Proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
Experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.

A good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
Familiarity with Financial Services and Fintech space is preferred.
Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).

Experience with Drift monitoring tools and frameworks.
Exposure to Knowledge Graphs or graph database applications.

Benefits

Competitive Compensation – competitive salary and share options
Time Off – Generous annual leave on top of bank holidays.
Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.

Health Insurance – Private family insurance with additional OPD coverage and top-up options.
Life & Accident Cover – Comprehensive accidental and life insurance protection.
Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.

Volunteering & Development Days – Paid days annually for volunteering or personal growth.
Learning & Development – Annual budget for books, courses, coaching, and more.
WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.

Home Office Setup – Contribution towards setting up your home office
Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent)