นักวิทยาศาสตร์ข้อมูลอาวุโส

Key Accountabilities

•    Lead development of high-impact predictive and prescriptive models across multiple domains (advanced segmentation, personalization, pricing, forecasting, advanced measurement)
•    Design and oversee complex experiments, including A/B and multivariate and tests
•    Drive uplift modeling and long-term value prediction to optimize targeting and offers
•    Research/adapt methods for hard problems; lead PoCs; scale viable solutions
•    Partner with business leaders to identify high-value opportunities for predictive model deployment
•    Co-design MLOps (feature store, experimentation, monitoring) with DE/P&T; ensure interoperability & governance
•    Apply causal inference techniques for marketing and product measurement.
•    Publish technical best practices and reusable frameworks

Education

Bachelor’s or Master’s in a quantitative field (ex: mathematics, statistics, data science) or an equivalent combination of education and work related experience

Experience

5-8 years of relevant work experience in Data Science with business-facing impact delivery   

Technical Skills and Knowledge

•    Strong SQL (advanced queries, stored procs, performance tuning) and Python programming skills
•    Advanced SQL, Python, and ML and LLM frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch, Gemini)
•    Proficiency deploying models in cloud environments (GCP - BigQueryML & Vertex AI, AWS SageMaker)
•    Proficiency in causal inference, optimization algorithms, and advanced experiment design
•    Expert in GCP/Vertex AI and MLOps orchestration tools
•    Advanced model governance and performance monitoring skills
•    Strong grasp of business impact modeling (ROI, LTV, incrementality)
•    Independent problem solver with strong critical thinking skills and business acumen
•    Strong statistical modeling (logistic/linear regression, time series, propensity modeling)
•    Experimental design (A/B, multivariate)
•    Feature engineering best practices