The Data Scientist will be responsible for transforming data into actionable insights that support Remal Ventures’ digital initiatives and business objectives. This role combines analytical expertise, creativity, and business acumen to design data solutions that improve decision-making and user engagement. The Data Scientist will collaborate closely with programming, design, marketing, and support teams to analyze trends, develop predictive models, and provide strategic recommendations that enhance product performance and operational efficiency.
Responsibilities: • Game Data Analysis: Analyze player engagement, retention (D1, D7, D30), session lengths, and churn patterns. Identify behavioral segments (e.g., new users, payers, whales, dormant users). Monitor in-game economy health — Aces spend/sink sources, inflation, and item usage. Track KPIs per feature (rooms, tournaments, events, store) and report insights. • Monetization & User Segmentation: Measure LTV, ARPU, ARPPU, conversion rate, and CAC by segment and product. Build predictive models for identifying churn and retaining high-value players. Work with LiveOps and Product to test offers, bundles, and pricing strategies. Analyze and recommend improvements to in-game purchases, ads, and VIP programs. • Experimentation & A/B Testing: Design and evaluate A/B tests for new features, game economy changes, or UX flows. Recommend test size, metrics, and ensure statistical significance. Present post-test insights and recommendations. • Data Infrastructure & Reporting: Work with backend engineers to ensure clean event tracking and schema consistency. Build dashboards and automated reports (e.g., in Looker Studio, Power BI, or Tableau). Maintain weekly KPI and trend reports for leadership and product teams. • Predictive Modeling & Machine Learning (if applicable): Develop models for churn prediction, spend forecasting, and player segmentation. Experiment with recommendation systems for offers, matchmaking, or tournaments to enhance user experience.
Required Competencies: • Programming: Python (pandas, NumPy, scikit-learn), SQL • Analytics: Statistical analysis, hypothesis testing, regression models • Data Visualisation: Power BI, Tableau, Looker Studio, or equivalent • Data Management: Google BigQuery, AWS Redshift, or similar platforms • Experimentation: A/B testing design, statistical significance, metrics tracking • Machine Learning (Optional/Advanced): Basics of classification, clustering, and regression Education/Qualification/ Certification and Work Experience: • Bachelor’s degree in computer science, or a related quantitative field. • 2–4 years of professional experience in data science, analytics roles. • Demonstrated experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. • Experience working with marketing analytics, user data, or digital platform metrics preferred. • Strong visualisation and reporting skills to communicate insights effectively to leadership teams. • Ability to work in a collaborative, fast-paced environment and manage multiple projects simultaneously
24 April 2025
Dammam, Saudi Arabia
Full-Time