Salt

Senior Data Scientist (Customer)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist (Customer) in London (Hybrid) with a contract length of more than 6 months, offering £60,000–£70,000 plus bonus. Key skills include Python, machine learning, SQL, and experience with customer data analytics.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
318
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🗓️ - Date
May 14, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Consulting #Regression #SQL (Structured Query Language) #Forecasting #Data Science #ML (Machine Learning) #AI (Artificial Intelligence) #Clustering #CRM (Customer Relationship Management) #Classification #Python
Role description
Senior Customer Data Scientist - Consulting London (Hybrid) £60,000–£70,000 + Bonus Permanent | Consulting (Customer & Data Analytics Practice) Overview A global consulting firm is building a new London-based Customer Data Science capability within its broader customer, digital, and marketing practice. The team focuses on combining customer experience, data science, and applied AI to help large consumer-facing organisations improve commercial performance, customer engagement, and marketing effectiveness. This is a newly scaling capability with strong investment and the opportunity to shape how advanced customer analytics and GenAI are applied in real-world client environments. The Role You will deliver hands-on data science and customer analytics work across a range of consumer-focused client projects. This is a delivery-heavy role combining technical data science with commercial problem solving and client-facing consulting, with a fast track to Management. Typical work includes: • Customer behaviour analysis and segmentation • Marketing and CRM performance analytics • Loyalty and retention modelling • Web, product, and digital analytics • Predictive modelling and forecasting • Applied GenAI / LLM use cases in customer and marketing contexts • Personalisation and optimisation initiatives Requirements • Strong hands-on Python and machine learning experience • Ability to build and deploy predictive models (classification, regression, clustering, forecasting) • Experience working with customer, CRM, marketing, or digital behavioural data • Exposure to GenAI / LLM-based applications (build, evaluate, or implement use cases) • SQL proficiency • Strong stakeholder communication skills • Ability to translate data insights into commercial recommendations • Experience in a consulting, agency, or in-house analytics environment Consulting experience is beneficial but not essential. Strong candidates from consumer-facing or agency backgrounds are welcome.