Data Scientist

Datatech; West End; Hybrid; GBP 65,000 - 75,000; Full time

Job summary

A leading analytics recruitment agency in the UK is seeking an experienced Data Scientist to develop predictive models and enhance customer experiences. The role requires expertise in machine learning and strong communication skills. This position offers a hybrid working model, with competitive salaries ranging from £65,000 to £75,000. Applicants should possess full UK working rights and relevant experience in customer marketing data science.

Qualifications

• Proven experience in applied statistics and machine learning techniques.
• Strong ability to transform analytical solutions into production-ready code.
• Experience in a global or multi-regional context is a plus.

Responsibilities

• Develop and implement predictive models to understand customer behaviour.
• Monitor and optimize model performance through continuous improvement.
• Translate complex analytical findings into clear, actionable insights.

Skills

Customer Marketing Data Science

Python

ML libraries (pandas, numpy, scipy)

Cloud platforms (GCP, AWS, Azure)

ML Ops

Excellent communication skills

Tools

Dataiku

Databricks

Job description

Data Scientist

Salaries in the region of £65,000 - £75,000 DoE

Hybrid working 2 days central London office

Job Reference J13031

Full UK working rights required / no sponsorship available

Immediate requirement - strong leadership skills

We are seeking for an experienced, passionate and highly motivated Data Scientist who will help discover the information hidden in vast amounts of customer data, and help make data driven decisions to deliver better products, service and relevance to the customers.

THE ROLE

Customer Science

• Develop and implement predictive models to understand drivers of customer behaviour, including purchase patterns, customer lifetime events and sentiment analysis
• Create sophisticated customer segmentation using behavioural, transactional, and demographic data
• Design and build predictive models to enhance personalized customer experiences across all channels
• Collaborate on design of test & learn methods to measure CRM initiatives' effectiveness
• Monitor and optimize model performance through continuous improvement cycles

Technical Implementation

• Transform analytical solutions into production-ready code
• Implement models within our existing technology stack
• Ensure scalability and efficiency of deployed solutions

Stakeholder Communication & Collaboration

• Translate complex analytical findings into clear, actionable insights
• Create compelling data visualizations to effectively communicate patterns and insights
• Partner with cross-functional teams to enhance CRM strategies
• Provide data-driven recommendations to improve customer engagement metrics

Skills

• Relevant experience in Customer Marketing Data Science including applied statistics and machine learning techniques (supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc)
• Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch)
• Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks.
• Experience with ML Ops, including model deployment, monitoring, and retraining pipelines.
• Ability to work cross-functionally with marketing, CRM, and engineering teams.
• Excellent communication skills
• Experience in a global or multi-regional context is a plus

If you would like to hear more, please do get in touch.

Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift / voucher scheme.

Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website : (url removed)