Data Science Engineer (Ref: 195974)

Data Science Engineer (Contract)

Industry: Software

Department: Data & Analytics – UK

Duration: April 2026 – October 2026

Day rate: Competitive

My Client is one of the world’s most innovative software companies, empowering billions of people globally to imagine, create, and deliver digital experiences. From creators and students to enterprises and nonprofits, Adobe’s solutions help organisations collaborate, innovate, and drive business growth.

As a Data Science Engineer, I support the Data Science team in developing data-driven models that directly influence sales strategy and business growth. This role involves working closely with senior stakeholders to analyse complex datasets, build predictive models, and deliver actionable insights that enable more effective customer engagement and revenue opportunities.

Key Responsibilities

• Develop and maintain rSAM models to identify and size revenue opportunities across the book of business.

• Conduct in-depth business analysis to identify drivers of performance gaps and recommend improvements.

• Partner with senior stakeholders to align analytical solutions with strategic growth priorities.

• Build and deploy predictive models, including propensity models, segmentation models, and forecasting solutions.

• Perform customer segmentation and channel segmentation to optimize engagement strategies and lifetime value.

• Design models for customer lifetime value (CLV) using survival analysis techniques.

• Evaluate and enhance the performance of sales campaigns through advanced analytics and model optimization.

• Collaborate with data engineering teams to productionize models and build scalable data pipelines.

• Automate model refresh cycles and account prioritization workflows.

• Translate complex analytical outputs into clear, actionable insights for business leaders and sales teams.

Tools & Technologies

• SQL (data querying, cleansing, integration, and summarization)

• Python

• Databricks

• Predictive modelling and machine learning techniques

• Customer segmentation and propensity modelling

Key Skills

• Advanced data analysis and statistical modelling

• Predictive modelling and machine learning

• Stakeholder communication and data storytelling

• Business strategy alignment through analytics

• Problem-solving in fast-paced environments