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Data Scientist - Job Opportunity at Entain

London, GB
Full-time
Mid-level
Posted: June 10, 2025
Hybrid
£55,000 - £75,000 per year. This estimate reflects the mid-level nature of the role, London market premiums, and the specialized combination of statistical modeling and business application skills required. The gaming industry typically offers competitive compensation packages, and Entain's established market position likely supports salaries in the upper portion of this range, particularly when considering the comprehensive benefits package and bonus structure.

Benefits

Comprehensive group bonus scheme providing performance-based financial rewards beyond base salary
Flexible hybrid working arrangement allowing 2 days remote work per week for improved work-life balance
Premium private medical insurance coverage ensuring comprehensive healthcare protection
Competitive pension scheme with employer matching up to 6% maximizing retirement savings
Flexible holiday trading system allowing purchase and sale of vacation days for personalized time-off management
Complimentary Unmind wellbeing app subscription supporting mental health and stress management
Additional 'It's Your Game' personal day off during holiday season for extended winter break
Two paid Entain & Enhance development days annually for professional and personal growth
Employee share save scheme providing equity participation and long-term wealth building opportunities
LinkedIn Learning premium subscription for continuous professional development and skill enhancement
Recognition and rewards program converting peer acknowledgment into tangible prizes and incentives

Key Responsibilities

Design and implement advanced statistical models to address critical business challenges, particularly in marketing optimization and customer analytics, directly impacting revenue generation and strategic decision-making
Develop and optimize sophisticated marketing mix models (MMMs) to quantify marketing channel effectiveness and campaign ROI, enabling data-driven budget allocation decisions worth millions
Build comprehensive incrementality testing frameworks to measure true business impact of strategic initiatives, ensuring accurate attribution of revenue drivers and preventing budget waste
Create robust statistical models for A/B testing and experimentation programs, establishing methodological standards that ensure reliable results for business-critical decisions
Collaborate directly with senior business stakeholders to translate complex analytical requirements into actionable solutions, serving as the bridge between technical capabilities and strategic objectives
Execute end-to-end data preparation and analysis using Python and SQL, managing large-scale datasets that inform company-wide strategic initiatives
Communicate complex statistical insights to C-level executives and non-technical stakeholders, influencing high-impact business decisions through clear data storytelling
Establish documentation standards and knowledge management practices ensuring reproducibility and scalability of analytical solutions across the organization
Monitor and optimize model performance in production environments, maintaining analytical frameworks that support real-time business operations
Drive innovation by researching and implementing cutting-edge statistical and machine learning techniques, positioning the organization at the forefront of data science capabilities
Partner with cross-functional teams including data engineers and senior data scientists to deploy models into production systems, ensuring seamless integration with business operations

Requirements

Education

Bachelor's or Master's degree in Statistics, Applied Mathematics, Econometrics, or related quantitative field

Experience

2-4 years of practical experience applying statistical methods to business problems

Required Skills

Strong foundation in statistics, hypothesis testing, regression analysis, and experimental design Experience with marketing mix modeling, incrementality testing, or causal inference Proficiency in Python for data analysis and statistical modeling (pandas, numpy, scipy, statsmodels) Familiarity with machine learning libraries such as scikit-learn Experience with SQL for data extraction and manipulation Demonstrated ability to translate analytical findings into business recommendations Track record of successful project delivery with measurable business impact Experience communicating technical concepts to non-technical audiences Understanding of business metrics and KPIs in a commercial setting
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Sauge AI Market Intelligence

Industry Trends

The gaming and sports betting industry is experiencing unprecedented digital transformation, with companies investing heavily in AI and machine learning capabilities to gain competitive advantages in customer acquisition, retention, and personalization. This shift is creating substantial demand for data scientists who can bridge the gap between advanced analytics and real-world business applications, particularly in areas like marketing optimization and customer lifetime value modeling. Marketing mix modeling and incrementality testing are becoming critical capabilities as digital advertising costs rise and privacy regulations limit traditional attribution methods. Companies are increasingly seeking data scientists who can implement sophisticated causal inference techniques to measure true marketing effectiveness, making this skillset particularly valuable in the current market environment. The convergence of traditional statistics with modern machine learning approaches is reshaping data science roles, with employers prioritizing candidates who can combine rigorous statistical foundations with practical implementation skills. This hybrid approach is especially important in regulated industries like gaming, where model interpretability and statistical rigor are essential for both business decisions and regulatory compliance.

Role Significance

The role likely operates within a team of 8-12 data professionals, including senior data scientists, data engineers, and analysts. As part of the CILA Data & AI function, the position benefits from working within a established analytics organization with clear career progression pathways and collaborative project structures.
This role represents a mid-level position with significant growth potential, positioned as a hands-on contributor who will have direct impact on strategic business decisions. The combination of technical responsibilities and stakeholder interaction suggests the role serves as a bridge between senior analytical leadership and business operations, providing substantial visibility and influence within the organization.

Key Projects

Comprehensive marketing mix modeling initiatives measuring multi-million pound marketing investments across digital and traditional channels, directly informing budget allocation decisions for major marketing campaigns Large-scale A/B testing programs evaluating product features, promotional strategies, and customer experience optimizations that impact user engagement and revenue generation across multiple markets Incrementality testing frameworks for promotional campaigns and customer acquisition strategies, helping quantify the true ROI of marketing investments and preventing budget waste on ineffective channels

Success Factors

Strong business acumen combined with technical excellence is crucial, as the role requires translating complex statistical concepts into actionable business recommendations that influence significant financial decisions. Success depends on the ability to understand commercial priorities and frame analytical solutions in terms of business value rather than technical sophistication. Exceptional communication skills are essential for effectively presenting analytical findings to diverse stakeholders, from technical teams to C-level executives. The ability to create compelling data narratives that drive decision-making will distinguish high performers in this role, particularly given the direct stakeholder interaction requirements. Adaptability and continuous learning mindset are critical given the rapidly evolving nature of both the gaming industry and data science methodologies. Success requires staying current with emerging techniques while maintaining focus on practical business applications rather than pursuing academic approaches that lack commercial relevance.

Market Demand

High demand. The combination of statistical expertise, marketing analytics specialization, and business application skills represents a particularly sought-after profile in the current market. The gaming industry's rapid digital evolution and increased focus on data-driven decision making creates strong demand for professionals who can translate complex analytics into measurable business value.

Important Skills

Critical Skills

Statistical modeling and experimental design expertise forms the foundation of this role's value proposition, as the ability to design and implement robust analytical frameworks directly impacts business decisions worth millions of pounds. This skillset differentiates data scientists from analysts and requires continuous development to stay current with emerging methodologies. Python programming proficiency with specific focus on statistical libraries (pandas, numpy, scipy, statsmodels) is essential for translating analytical concepts into practical implementations. This technical foundation enables the rapid prototyping and deployment of models that support real-time business operations. Business communication and stakeholder management skills are critical for success, as the role's impact depends entirely on the ability to influence decision-making through clear presentation of analytical insights. This soft skill often determines whether technical expertise translates into career advancement and organizational influence.

Beneficial Skills

Machine learning and advanced analytics capabilities provide opportunities for innovation and problem-solving beyond traditional statistical approaches, particularly important as the industry evolves toward more sophisticated predictive modeling and personalization strategies Cloud platform experience (AWS, Azure, GCP) becomes increasingly valuable as organizations migrate analytics workloads to scalable cloud infrastructure, offering opportunities for technical leadership and system architecture contributions Domain expertise in gaming or similar digital industries accelerates impact and provides context for analytical solutions, enabling more nuanced interpretation of results and more relevant recommendations for business stakeholders

Unique Aspects

The role offers direct exposure to the fast-paced gaming and sports betting industry, providing opportunities to work with unique datasets and business challenges that differ significantly from traditional e-commerce or technology companies, including real-time decision making and high-volume transaction analysis
Focus on marketing mix modeling and incrementality testing represents specialized expertise that is increasingly valuable across industries, providing transferable skills that extend well beyond the gaming sector and position the role holder as an expert in causal inference and marketing analytics
The combination of statistical rigor with practical business application creates a distinctive professional profile that bridges academic statistical training with commercial analytics, offering career flexibility across multiple industries while building deep expertise in applied statistics

Career Growth

Career progression to senior individual contributor roles typically occurs within 2-3 years for high performers, with advancement to leadership positions possible within 4-5 years. The specialized nature of marketing analytics and the gaming industry's rapid growth create accelerated progression opportunities for professionals who demonstrate both technical excellence and business impact.

Potential Next Roles

Senior Data Scientist positions focusing on advanced modeling and team leadership responsibilities, typically involving oversight of junior team members and ownership of complex analytical initiatives Lead Data Scientist or Principal Data Scientist roles with strategic responsibility for analytical frameworks and methodological standards across business units Analytics Manager or Data Science Manager positions combining technical expertise with people management and strategic planning responsibilities Business Intelligence leadership roles focusing on organizational analytics strategy and cross-functional collaboration with senior business leaders

Company Overview

Entain

Entain is a major global sports betting and gaming entertainment company that operates some of the world's most recognized brands in the industry. The company has established itself as a technology-forward organization with significant investments in digital platforms and data-driven capabilities, positioning analytics and AI as core strategic differentiators in a highly competitive market.

Entain holds a strong position as one of the leading players in the global gaming and sports betting market, with operations across multiple regulated jurisdictions and a diverse portfolio of brands. The company's emphasis on technology and data science reflects its strategy to maintain competitive advantages through innovation rather than relying solely on traditional marketing and promotional approaches.
The London location positions this role at the heart of Entain's European operations, providing exposure to both UK market dynamics and broader international strategic initiatives. London serves as a key hub for the company's data and analytics capabilities, offering collaboration opportunities with global teams and access to cutting-edge projects across multiple markets.
Entain emphasizes a performance-driven culture that balances individual achievement with collaborative team success. The company's focus on putting 'people first' while driving innovation suggests an environment that supports professional development and recognizes individual contributions, particularly important for technical roles where expertise and creativity are key differentiators.
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