Data Analyst

What You'll Do:

• Analyze performance across marketing channels (paid media, organic, CRM, referral, affiliates) to identify growth and retention opportunities.
• Partner with the Growth and CRM teams to evaluate acquisition funnels, retention drivers, and customer lifetime value (LTV).
• Build and maintain automated dashboards and reports in Power BI to track key KPIs.
• Support experimentation and testing (A/B, holdout, incrementality) to measure campaign effectiveness and optimize ROI.
• Translate complex data findings into actionable recommendations that inform marketing and audience strategies.
• Develop practical, data-driven models and frameworks to estimate user LTV, churn risk, and player segmentation, helping guide marketing and retention strategies.
• Use statistical and exploratory techniques to identify behavioral patterns that can improve acquisition, engagement, and monetization.
• Apply machine learning or regression-based methods when useful — not just for modeling, but to enhance day-to-day decision-making with forward-looking insights.
• Work in tandem with decision-makers across departments to understand their goals and proactively identify opportunities to leverage data for developing new insights and enhancing business results.
• Assist in regulatory and state reporting by ensuring data accuracy, completeness, and timely delivery of required reports.
• Ensure data consistency, governance, and alignment of key metrics across the organization.
• Write efficient SQL queries to extract, transform, and analyze large datasets from data warehouses (e.g., BigQuery).
• Develop clean, intuitive dashboards and visualizations that make complex data accessible to stakeholders.
• Communicate findings clearly to both technical and non-technical audiences, turning data into narratives that drive action.

About You:

• Experience: 3+ years in data analytics, business intelligence, or growth analytics, ideally within B2C industries such as gaming, sports, or fintech.
• Technical Skills: Advanced SQL and data modeling expertise. Strong experience with Power BI (preferred) or similar visualization tools (Tableau, Looker). Exposure to predictive modeling and machine learning concepts (e.g., regression, clustering, LTV, churn, or cohort analysis). Familiarity with marketing platforms and analytics tools (Google Analytics, Singular, AppsFlyer, Meta Ads, Google Ads, CRM/email platforms).
• Analytical Mindset: You can connect marketing performance to business outcomes and uncover the “why” behind the numbers.
• Communication: Excellent at translating technical findings into clear, strategic recommendations.
• Curiosity & Initiative: Proactive, detail-oriented, and eager to explore new ways data can improve decision-making.
• Bonus Points: Experience with Python or R and predictive model deployment.