Data Scientist

Salt; United Kingdom; On-site; GBP 100,000 - 125,000; Full time

Job summary

A leading technology consulting firm in the United Kingdom seeks an experienced Senior Data Scientist to develop analytics solutions focused on customer behavior and engagement. This hybrid role involves leading projects, building predictive models, and partnering with cross-functional teams to optimize marketing strategies. Ideal candidates will have 7+ years of experience, strong skills in Python and SQL, and a relevant advanced degree.

Benefits

Supportive and innovative data culture

Continuous learning opportunities

High-impact, fast-paced environment

Qualifications

• 7+ years in data science or analytics focusing on customer behavior.
• Proven track record of creating measurable business value.
• Experience in B2C, e-commerce, subscription, retail, or fintech industries.

Responsibilities

• Lead customer-centric analytics projects.
• Build and maintain predictive models.
• Conduct analyses on customer journeys.
• Optimize campaigns with Marketing and Product teams.
• Own the lifecycle of models from deployment to monitoring.
• Mentor junior data scientists.

Skills

Python (pandas, scikit-learn, XGBoost, LightGBM)

SQL for data extraction

Customer analytics techniques

BI tools (Tableau, Power BI)

Cloud platforms (AWS, GCP, Azure)

Education

MSc or PhD in a quantitative field

Tools

Tableau

Power BI

Job description

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Senior Data Scientist – Customer & Behavioural Analytics

Hybrid Working – 1 day in the office circa every 2 weeks.

Role Summary

We are seeking a commercially minded Senior Data Scientist to lead the development of advanced analytics and machine learning solutions focused on customer behavior, personalization, and lifecycle management. Your work will directly impact customer retention, engagement, and lifetime value, helping the business make smarter, data-driven decisions at scale.

Key Responsibilities

• Lead customer-centric analytics projects across retention, segmentation, churn prediction, product usage, and personalization
• Build and maintain predictive models ( churn, CLV, next-best action, recommendation systems) and translate insights into business value
• Conduct deep-dive analyses into customer journeys, identifying behavioral trends and opportunities for intervention
• Partner with Marketing, Product, and Customer Success to optimize campaigns, targeting strategies, and user engagement
• Own the end-to-end lifecycle of models: from problem framing to deployment and monitoring
• Present analytical findings and strategies to stakeholders in a compelling and actionable way
• Mentor junior data scientists and contribute to the evolution of data science standards and practices

Key Skills & Technologies

Technical:

• Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.)
• Proficient in SQL for complex customer data extraction and manipulation
• Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing, uplift modeling
• Familiarity with BI tools ( Tableau, Power BI) for communicating customer insights
• Comfortable working with large datasets from sources like CRM, web analytics, product telemetry, etc.
• Exposure to cloud platforms (AWS, GCP, Azure) and modern data pipelines ( Airflow, dbt) is a plus

Soft Skills:

• Business-oriented thinker with strong communication skills
• Able to clearly explain complex models to non-technical audiences
• Skilled in stakeholder engagement and translating analytics into action
• Curious, collaborative, and proactive in driving change

Qualifications

• 7+ years in data science or analytics with a strong focus on customer behavior
• MSc or PhD in a quantitative field (Statistics, Data Science, Computer Science, Applied Math)
• Proven track record of creating measurable business value through customer-focused models and analytics
• Experience working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage

Nice to Have

• Experience with NLP for customer feedback or support ticket analysis
• Exposure to MLOps for model deployment and monitoring
• Familiarity with tools like Amplitude, Mixpanel, or Google Analytics

Why Join Us?

• Shape data-driven strategy for how we understand and engage with our customers
• Collaborate with cross-functional teams and influence C-level decision-making
• Work in a high-impact, fast-paced environment where your work matters
• Supportive and innovative data culture with continuous learning opportunities

Please do send across to me the most up to date CV to

*Rates depend on experience and client requirements