Data Scientist

- Problem definition for ad delivery optimization and the design of KPIs/metrics, along with observability (dashboards and alerts). 

- Data preprocessing, feature engineering, modeling, and offline evaluation (including simulation) for price optimization, CTR/CVR and value prediction, and creative optimization. 

- Online deployment and experiment design: A/B tests/bandits, calibration, rollout strategy planning, effectiveness evaluation, and continuous improvement. 

- Production operations and MLOps: building training/inference pipelines; monitoring and drift detection; model updates and automated rollback; quality and privacy governance. 

- Collaboration with internal stakeholders (product, engineering, sales/operations) on requirements definition, decision support, documentation, and knowledge sharing. 

- 3+ years of hands-on experience in data analysis and machine learning using Python and SQL; proficiency with Pandas/NumPy/scikit-learn and data visualization tools 

- Experience processing large-scale data (e.g., Spark, BigQuery) and building reproducible analytics environments (using notebooks and repositories together, code reviews, testing) 

- Solid foundation in statistics, probability, causal inference, and experimental design (hypothesis testing, sampling, A/B test design and analysis, effect size estimation) 

- Experience developing machine learning models (regression, classification; tree-based methods/GBDT/logistic regression/simple neural networks) with rigorous evaluation design (offline/online metrics, calibration) 

- Foundational knowledge of online/digital advertising (CTR/CVR prediction, bidding and budget pacing, ad serving control, KPI optimization) or practical optimization experience in adjacent domains 

- Feature engineering oriented toward price and serving optimization use cases; data quality management, leakage prevention, and handling delayed/late-arriving labels 

- Production experience (model deployment, scheduling/pipeline operations, monitoring, implementing and operating drift detection) 

- Communication skills for collaborating with stakeholders on requirements definition, analysis design, and decision support (including explaining and visualizing deliverables)