What You'll Do
Design, build, and improve ML/AI models across domains – recommendation systems, image recognition, chatbots, and beyond.
Own the full ML lifecycle: data preprocessing, feature engineering, training, validation, and deployment to production.
Build evaluation pipelines that prove performance, scalability, and consistency – and that the rest of the team can reuse.
Apply generative AI and LLMs to improve existing workflows and identify new product opportunities.
Partner with Product, Engineering, and Analytics to keep modeling work tied to real business outcomes.
Translate complex model behavior and findings into insights stakeholders can act on.
Bring technical judgment to the team – share what you learn, and help keep practices consistent across different models and domains.
BSc or higher in Computer Science, Mathematics, Statistics, or related fields.
4+ years of hands-on experience as a Data Scientist, ideally within mobile, gaming, or social network industries.
Proven experience with AI/ML frameworks and toolkits (Scikit-learn, TensorFlow, PyTorch, LangChain, etc.)
Familiarity with MLOps best practices, model versioning, experiment tracking, and continuous deployment.
Strong knowledge of machine learning techniques: Classification, regression, segmentation, reranking, model interpretability
Solid background in data analysis and statistics; ability to design experiments and interpret results.
Experience working in cloud environments, especially Google Cloud Platform (GCP) – BigQuery, GCS, Vertex AI (a plus).
Comfortable working in fast-paced, production-critical environments with a sense of ownership and accountability.
