Data Scientist - Partnership Optimisation

Contract: Full-time

About Protect Group

Protect Group, established in 2016, is an innovative global technology leader enhancing customer experiences and revenue opportunities for businesses through AI-driven solutions. With over 400 partners across 75+ countries, we provide an intuitive widget that seamlessly integrates with online sales platforms, dramatically improving customer satisfaction and boosting ancillary revenue through our core Refund Protection product.

Our culture is defined by ambition, innovation, and excellence. Our Protect People embody these values, making a significant impact across sectors including Travel, OTAs, Hospitality, Transportation, and Ticketing.

Role Overview

We are seeking a commercially-minded Data Scientist to act as a strategic lead for our Partnership teams. In this pivotal role, you will function as a Partnership Optimiser, tasked with maximising the value and performance of our external partnerships.

You will bridge the gap between complex data and commercial strategy, working directly with external stakeholders (OTAs, event platforms, hospitality providers) and internal partnership managers. You will build scalable solutions, drive A/B testing, and deploy web applications that empower non-technical teams to make data-driven decisions.

Key Responsibilities

Strategic Partnership Optimisation

• Strategy Lead: Act as the analytical lead for the partnerships team, using large, complex datasets to define strategies that maximise revenue and conversion rates for our products.
• External Engagement: Present complex analytical findings and commercial models directly to external stakeholders and C-suite, articulating value clearly and effectively.
• Hypothesis & A/B Testing: Design and execute rigorous A/B tests and hypothesis testing frameworks to optimise pricing, placement, and UI/UX within partner booking flows.

Technical Execution & Innovation

• Commercial Modelling: Develop sophisticated commercial models to forecast demand, price elasticity, and revenue impact across diverse sectors.
• Tool Development: Build and deploy interactive Web Apps and dashboard (e.g., Streamlit, Dash, Tableau) and toolkits to automate data access and reporting, driving the adoption of technical solutions across internal partnership teams.
• Generative AI: Leverage Gen AI to automate insights generation and enhance partner reporting capabilities.

Data Engineering & Architecture

• Scalable Solutions: Establish scalable data solutions and pipelines; you will be responsible for strong data engineering tasks to ingest, clean, and structure data from varied sources.
• Pipeline Management: Oversee the end-to-end data lifecycle within Azure, ensuring robust MLOps practices.

Required Skills & Experience

Education & Technical Foundations

• Degree: Bachelor’s or Master’s degree in STEM, Computer Science, Mathematics, Statistics, or a related quantitative field.
• Scientific Python Ecosystem: Proficiency in Python for data science (pandas, numpy, scipy) and machine learning (sklearn, XGBoost, CatBoost, PyTorch).
• Data Engineering: Strong experience in SQL and data engineering principles (ETL/ELT), with the ability to handle large, complex datasets independently.
• Collaboration: Proficient in Git and comfortable working with Excel for stakeholder data exchange.
• Cloud & MLOps: Hands-on experience with Azure, MLOps pipelines, and API frameworks.

Analytical & Commercial Skills

• Experimentation: Deep understanding of statistical methods, specifically A/B testing, hypothesis testing, and probability theory.
• Web App Development: Proven ability to build internal tools and web applications to visualise data and run simulations.
• Revenue Optimisation: Experience in pricing optimisation, elasticity modelling, and commercial strategy.
• Generative AI: Familiarity with LLMs and Gen AI applications in a business context.

Communication & Soft Skills

• Stakeholder Management: Strong communication skills with experience presenting to external partners and stakeholders.
• Translation: The ability to translate complex technical analysis into interpretable, clear, and actionable commercial insights.
• Adoption Driver: A proactive approach to training and encouraging non-technical teams to adopt data-driven toolkits.

Why Protect Group?

• Impact: You won’t just analyse data; you will directly shape the commercial success of our partners in the a wide range of sectors.
• Innovation: Work at the cutting edge, utilising Gen AI and building custom Web Apps that drive business operations.
• Growth: Join a rapidly scaling tech company revolutionising global industries with a talented team dedicated to continuous improvement.

Ready to Join Us?

If you are a Data Scientist with the mindset of a commercial strategist and the skills of an engineer, we want to hear from you! Submit your CV today.

• Degree: Bachelor’s or Master’s degree in STEM, Computer Science, Mathematics, Statistics, or a related quantitative field.
• Scientific Python Ecosystem: Proficiency in Python for data science (pandas, numpy, scipy) and machine learning (sklearn, XGBoost, CatBoost, PyTorch).
• Data Engineering: Strong experience in SQL and data engineering principles (ETL/ELT), with the ability to handle large, complex datasets independently.
• Collaboration: Proficient in Git and comfortable working with Excel for stakeholder data exchange.
• Cloud & MLOps: Hands-on experience with Azure, MLOps pipelines, and API frameworks.

Analytical & Commercial Skills

• Experimentation: Deep understanding of statistical methods, specifically A/B testing, hypothesis testing, and probability theory.
• Web App Development: Proven ability to build internal tools and web applications to visualise data and run simulations.
• Revenue Optimisation: Experience in pricing optimisation, elasticity modelling, and commercial strategy.
• Generative AI: Familiarity with LLMs and Gen AI applications in a business context.

Communication & Soft Skills

• Stakeholder Management: Strong communication skills with experience presenting to external partners and stakeholders.
• Translation: The ability to translate complex technical analysis into interpretable, clear, and actionable commercial insights.
• Adoption Driver: A proactive approach to training and encouraging non-technical teams to adopt data-driven toolkits.

About Protect Group

Protect Group, established in 2016, is an innovative global technology leader enhancing customer experiences and revenue opportunities for businesses through AI-driven solutions. With over 400 partners across 75+ countries, we provide an intuitive widget that seamlessly integrates with online sales platforms, dramatically improving customer satisfaction and boosting ancillary revenue through our core Refund Protection product.

Our culture is defined by ambition, innovation, and excellence. Our Protect People embody these values, making a significant impact across sectors including Travel, OTAs, Hospitality, Transportation, and Ticketing.