Data Scientist - London

Candour Solutions; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Up to 20% bonus

10% company pension contributions

Job summary

TeamCandour, on behalf of a globally active financial services organisation, is seeking a Data Scientist to join a growing London team. Based in London with hybrid working, you will collaborate with data scientists, engineers and analysts to deliver MVP solutions that scale.

You will work with stakeholders across business functions on opportunities in decision-making, pricing, customer intent and monitoring.

Qualifications

• Strong Python programming skills.
• Experience with test-driven development (TDD).
• Familiarity with version control and IT delivery tools.
• Experience across the data science lifecycle (model development, deployment, monitoring).
• Predictive or prescriptive analytics experience.

Responsibilities

• Apply data science lifecycle principles across new projects from design to deployment.
• Develop production ML models and monitor their performance.

Skills

Python

TDD

Version control

ML/DM

Communication

Tools

pytest

Git

CI/CD

Cloud deployment

Job description

#TeamCandour have been retained by a thriving, global financial services organisation to add a further Data Scientist to help turn data into practical business value as part of a rapidly growing team. Based in London, this permanent role offers hybrid working. You will join a core team of data scientists, engineers and analysts, working in small teams with a two-week review cycle and an approach focused on developing minimum viable solutions that can be scaled.

You will work with stakeholders across business functions to identify opportunities in areas including decision-making, pricing, customer intent and monitoring. The role combines hands‑on technical work with clear communication: you will help colleagues understand where data science can make a difference, shape effective solutions and take them through to implementation. It will suit someone who enjoys collaboration, tackling varied business challenges and continuing to develop their data science practice.

As well as offering an unrivalled career opportunity, the organisation has one of the most comprehensive benefits packages we have seen including:

Up to 20% bonus

10% company pension contributions

Essential technical skills:

Strong Python programming skills and willingness to learn software‑development best practice.

Experience with test‑driven development (TDD), using pytest or another testing framework.

Familiarity with version control and IT delivery tools.

Experience across the data science lifecycle, including model development, deployment, monitoring and maintenance.

Predictive or prescriptive analysis experience, including predictive modelling, machine learning or data mining.

Ability to identify applications of machine learning to business problems and communicate findings clearly.

Experience with cloud deployment, commercial development and tuning of machine learning models, API development, SQL, DevOps, MLOps or CI/CD would be useful. A relevant graduate or postgraduate qualification, or equivalent experience in a discipline such as engineering, mathematics, physics or statistics, is also welcomed.

Key responsibilities: Data science lifecycle

Apply data science product lifecycle principles across new projects, from design and exploratory data analysis through to model building, evaluation, deployment, monitoring and maintenance. You will develop scientific approaches to business problems, assess the suitability of data and methods, and help ensure solutions are useful in practice. Work may involve changing contexts and a variety of internal and third‑party data, in both large and small datasets. You will contribute to solutions using machine learning, statistical modelling and other relevant techniques, taking an iterative approach to delivering value and developing work from an initial solution towards a more complete implementation.

Contribute to the development of production data science models and take an active role in their ongoing performance and lifecycle management. This includes monitoring how models perform and helping to retrain, optimise or upgrade them as needed. You will bring experience in predictive or prescriptive analysis, such as predictive modelling, machine learning or data mining, and use it to generate useful business insights. You will also help identify where machine learning can address a business problem, assess potential approaches and communicate findings clearly to the audiences who need to act on them.