Forsyth Barnes

Data Science Engineer (Ref: 195974)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Science Engineer (Contract) from April 2026 to October 2026, offering a competitive day rate. Key skills required include SQL, Python, and predictive modeling. Experience in business analysis and customer segmentation is essential.
🌎 - Country
United Kingdom
πŸ’± - Currency
Β£ GBP
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
March 13, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Unknown
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Reading, England, United Kingdom
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🧠 - Skills detailed
#Strategy #Data Analysis #Model Optimization #Datasets #Python #Databricks #Storytelling #Data Engineering #Customer Segmentation #Forecasting #Scala #Data Science #Data Pipeline #Data Storytelling #ML (Machine Learning) #Business Analysis #SQL (Structured Query Language)
Role description
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 β€’ Develop and maintain rSAM models to identify and size revenue opportunities across the book of business. β€’ Conduct in-depth business analysis to identify drivers of performance gaps and recommend improvements. β€’ Partner with senior stakeholders to align analytical solutions with strategic growth priorities. β€’ Build and deploy predictive models, including propensity models, segmentation models, and forecasting solutions. β€’ Perform customer segmentation and channel segmentation to optimize engagement strategies and lifetime value. β€’ Design models for customer lifetime value (CLV) using survival analysis techniques. β€’ Evaluate and enhance the performance of sales campaigns through advanced analytics and model optimization. β€’ Collaborate with data engineering teams to productionize models and build scalable data pipelines. β€’ Automate model refresh cycles and account prioritization workflows. β€’ Translate complex analytical outputs into clear, actionable insights for business leaders and sales teams. Tools & Technologies β€’ SQL (data querying, cleansing, integration, and summarization) β€’ Python β€’ Databricks β€’ Predictive modelling and machine learning techniques β€’ Customer segmentation and propensity modelling Key Skills β€’ Advanced data analysis and statistical modelling β€’ Predictive modelling and machine learning β€’ Stakeholder communication and data storytelling β€’ Business strategy alignment through analytics β€’ Problem-solving in fast-paced environments