

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
-
🏝️ - 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.
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.






