Data Scientist

Job Title: Data Scientist

Salary: £55,000 - £65,000

Location: London (Hybrid)

Overview

We are seeking a Data Scientist to join a growing data team within a technology-led SaaS software company. This role will play a key part in developing and deploying data-driven models and insights that directly support product development, customer experience, and commercial decision-making.

The successful candidate will have strong experience in statistical modelling, machine learning, and experimentation, with the ability to work closely with product and engineering teams to deliver practical, scalable solutions.

Key Responsibilities

Data Science & Modelling

• Develop, test, and deploy statistical and machine learning models to support product features and business decision-making.
• Apply predictive modelling, classification, and optimisation techniques to real-world problems.
• Perform exploratory data analysis to identify trends, patterns, and opportunities for improvement.

Experimentation & Insights

• Design, run, and analyse experiments such as A/B tests and feature tests.
• Interpret results to inform product strategy, user behaviour, and performance optimisation.
• Quantify the impact of data-driven initiatives and communicate findings clearly.

Data Analysis & Engineering Collaboration

• Work with large, complex datasets using Python and SQL.
• Collaborate closely with software engineers to ensure models are production-ready and scalable.
• Support the development of data pipelines and model monitoring processes.
• Partner with Product Managers, Engineers, and other stakeholders to translate business needs into analytical solutions.

Qualifications & Experience

• ~3+ years' commercial experience using data science and analytics to drive product or business decisions.
• Strong Python skills for data analysis, modelling, and experimentation; working knowledge of SQL.
• Solid grounding in statistics, machine learning, and predictive modelling, including classification, regression, and clustering techniques.
• Experience designing, running, and evaluating experiments (e.g. A/B testing) to measure product or feature effectiveness.
• Ability to navigate large, complex, or ambiguous datasets and translate analysis into clear, actionable insights.
• Experience using common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow, or similar).
• Exposure to cloud-based data or ML platforms (AWS, GCP, Azure or similar).
• Strong data visualisation and communication skills, with the ability to present insights clearly to technical and non-technical stakeholders.
• Product-focused mindset with an interest in modern AI techniques, such as LLMs.

Benefits

• Hybrid working model
• Competitive salary and performance-related incentives
• Learning and development opportunities
• Supportive and inclusive company culture

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