Marketing Scientist & BI Manager - iGaming

Our client is a casino resort business that is taking bold strides into the digital space having already launch online sportsbook to huge success. They are now seeking to build up a successful iGaming operation – you’ll get to work across both! This is your chance to join early and make a huge impact. You’ll be the second person into this new Marketing Data team. You’ll sit with the digital team in Philadelphia and collaborate in person 2 days per week – Tue & Wed.

Why join?

• Learn from one of the most highly skilled data experts in sports betting & iGaming
• 20 Days PTO plus public holidays
• Period between Christmas & New Year off subject to business needs and manager approval
• Healthcare, dental & vision
• Company sick pay; 10 days in first 12 months, increasing to 15 there after
• Day off on your birthday
• Bonus
• Work From Anywhere for up to 30 days
• Access to a global team of colleagues and experts across a range of topics
• Opportunities work on projects in areas of the business that don’t directly relate to Marketing or Data – always be learning culture!

Interested? Read on!

For this crucial role we’re seeking someone who has a natural curiosity and is driven by a passion for uncovering insights that drive business decisions. The ideal candidate will be self-motivated and possess exceptional critical thinking skills, keen attention to detail, and have a relentless desire to continuously learn and grow. In this role, you will work closely with stakeholders while analyzing complex data sets and developing actionable insights. You will also partner with the VP of Data & Growth to help create a data driven culture across the company.

As a Marketing Scientist, you will own media mix modelling and attribution to optimize marketing spend and effectiveness. You will stay up to date with industry best practices, especially as data privacy evolves, ensuring compliance and innovation in Apple App Tracking & Transparency (ATT) and mobile attribution. Additionally, you will provide data-driven recommendations to maximize Return on Ad Spend (ROAS) and collaborate with CRM teams to maximize player Lifetime Value (LTV) and minimize customer churn.

Essential Duties & Responsibilities:

• Lead and own weekly and monthly business review presentations, delivering detailed analysis of business performance across marketing, operations & product. As well as providing actionable insights to drive strategic decision-making.
• Develop, implement, and optimize multi-touch attribution models to accurately measure the effectiveness of various marketing channels.
• Design and execute media mix modelling to inform budget allocation and maximize ROI across all marketing channels.
• Analyze user data and build and/or maintain various models such as player cohorting, lifetime value, and others.
• Collaborate with marketing, operations, and product teams to understand business objectives and translate them into data-driven strategies.
• Analyze large datasets to uncover trends, patterns, and insights that drive strategic marketing decisions.
• Create and maintain dashboards and reports to monitor performance and provide actionable insights to stakeholders.
• Stay updated with the latest trends and advancements in data science, analytics, and marketing technology.
• Ensure data quality and integrity by establishing and enforcing best practices for data collection, processing, and analysis.
• Present findings and recommendations to senior leadership and other stakeholders in a clear and concise manner.
• Drive the development and implementation of new predictive models and machine learning algorithms to enhance marketing efforts.

Education, Qualifications & Experience:

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Marketing, or a related field.
• Minimum of 3 years of experience in analytics or data science role.
• Strong proficiency in working with data warehouses with high degree of comfort writing SQL
• Strong proficiency in statistical analysis, data mining, and predictive modeling techniques (Python or R).
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Experience with digital marketing platforms (Google Analytics, Facebook Ads, etc.) and understanding of various marketing channels (search, display, social, TV, OOH).

Preferred Experience:

• Experience using machine learning techniques to build eLTV models.
• Experience working for a mobile app or Direct to Consumer brand.
• Familiarity and experience with attribution reporting in a post Apple’s ATT ecosystem.