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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** FPT INC - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $29,120.0 - $52,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Airflow, Big Data, BigQuery, Mobile Application Development, Data Governance, Dataspaces, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Workflow Management Systems, Usage Analysis, Data Processing, Pytorch, Deep Learning, Firebase, Scikit Learn, Information Technology, Data Analytics, Xgboost, Performance Monitor, Free and Open-Source Software, Machine Learning Operations, Software Version Control - **Published:** July 14, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p491ex3zuq ## About the Role * Bachelor's degree or above in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, or related quantitative disciplines. * 3+ years of hands-on DS work with models shipped to production (not just research or competition work) * Experience building and deploying end-to-end Machine Learning solutions in production environments. * Experience working with large-scale datasets and translating insights into business impact. * Experience in mobile gaming, digital products, or consumer applications is a strong advantage. Technical Skills * Minimum Qualifications: * Core Languages: Strong proficiency in Python and SQL for data manipulation and model development. * Data Science Fundamentals: Deep understanding of statistical analysis, probability, hypothesis testing, and rigorous experimental design. * Machine Learning: Deep understanding of Machine learning and deep learning algorithms and hands-on experience building, training, and tuning models using frameworks (from classic libraries like Scikit-learn/XGBoost to deep learning tools like PyTorch/TensorFlow). * MLOps Practices: Familiarity with the end-to-end ML lifecycle, including model deployment, performance monitoring, version control, and pipeline reproducibility. * Preferred Qualifications: * Experience with workflow orchestration tools like Apache Airflow. * Familiarity with modern data ecosystems and warehouses (e.g., DBT, BigQuery, Firebase). * Active participation in the data science community, evidenced by Kaggle achievements or open-source contributions. Soft Skills * Strong analytical thinking and problem-solving skills. * Curious mindset with a passion for learning and experimenting with new technologies. * Ability to communicate complex ideas effectively to diverse audiences. * Ownership mindset with the ability to work independently and drive initiatives from ideation to execution. * Collaborative, proactive, and willing to share knowledge with teammates. * Passion for games and a genuine interest in understanding player behavior. ## Description * Design, develop, deploy, and maintain Machine Learning models to solve business and product challenges. * Build predictive models related to player behavior, including retention, churn prediction, pLTV/ breakeven estimation, and conversion propensity. * Build pLTV / breakeven prediction models at player and cohort level to drive UA decisions (bidding, scaling, killing campaigns) * Explore and prototype new ML approaches to improve game performance and operational efficiency. * Develop scalable ML pipelines and ensure models can be deployed into production environments. Product Analytics * Analyze large-scale player behavioral data to uncover actionable insights and identify growth opportunities. * Monitor and optimize key game KPIs such as Retention, DAU, MAU, ARPDAU, Conversion, Session Length, and Lifetime Value (LTV). * Partner closely with Product Managers and Game Designers to optimize game progression, level difficulty, economy balancing, and feature performance. * Translate business questions into analytical frameworks and data-driven recommendations. Experimentation & Optimization * Design, execute, and evaluate A/B tests to measure the impact of game features, economy adjustments, live operations, and monetization initiatives. * Apply statistical methodologies to validate hypotheses and support decision-making. * Develop experimentation best practices and improve the company's testing capabilities. Collaboration & Data Culture * Work cross-functionally with Product, Game Design, BI, UA, Engineering, and Leadership teams. * Present complex findings in a clear and compelling manner to both technical and non-technical stakeholders. * Promote a strong data-driven culture and advocate for best practices in coding, experimentation, documentation, and data governance. * Share knowledge, mentor teammates when needed, and continuously explore emerging technologies and methodologies. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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