Job
Description
About Pocket Entertainment Pocket Entertainment is revolutionizing entertainment through immersive storytelling. With millions of users worldwide, we're building the future of entertainment — blending human creativity with cutting-edge AI. Now, we’re expanding our global footprint. Let’s reimagine global entertainment — powered by AI and fueled by imagination. Work on category-defining AI products reshaping entertainment that operate at massive scale: millions of users, billions of minutes consumed. Collaborate with some of the best engineers, AI researchers, and creators globally. Mission of the role As a Senior Principal Data Scientist at Pocket FM, you will play a pivotal role in driving innovation in recommendation systems , user personalization , and content strategy . You will lead high-impact initiatives to understand user behavior, predict preferences, and enhance engagement through intelligent content delivery. This is a hands-on leadership role where you will set the technical vision, guide the roadmap, influence strategy, and mentor a high-performing data science team. Key responsibilities: Design and deploy machine learning models for recommendations, personalization, ranking, and user behavior prediction Tackle high-impact challenges across personalization, churn prediction, LTV modeling, creator analytics, and platform growth Partner with engineering, product, and content teams to align modeling efforts with business impact Lead the full ML lifecycle: prototyping, experimentation, A/B testing, deployment, and monitoring Translate large-scale user behavior data into actionable insights and strategies for content discovery and retention Mentor and guide junior and senior data scientists, fostering a culture of technical excellence, innovation, and continuous learning Conduct in-depth data analysis and exploratory research to uncover actionable insights, understand user trends, and identify new opportunities for product improvement and growth Drive MLOps best practices including model monitoring, versioning, and lifecycle management Stay current with advances in ML/NLP and apply them to improve recommendation quality and user satisfaction Qualifications: Advanced degree (PhD or Master’s) in CS, ML, Stats, or related field 12+ years of experience building and deploying ML models in production Expertise in recommender systems, personalization, ranking, or user modeling Strong Python skills and deep experience with ML frameworks (e.g., PyTorch, TensorFlow, XGBoost) Solid grounding in experimentation, A/B testing, and statistical inference Experience with big data tools (Spark, Databricks) and cloud platforms (AWS/GCP) Strong analytical and creative problem-solving skills Strong communication and cross-functional collaboration skills Bonus Points: Experience with NLP techniques applied to text or audio data Contributions to open-source ML projects or research publications Familiarity with generative AI models and their applications Show more Show less
