Statistics Validator Jobs in Bothell, WA (NOW HIRING)

Job Summary:
Microsoft is a leading technology company focused on empowering individuals and organizations. They are seeking a Senior Applied Scientist to drive modeling and data innovations for ad interaction outcome prediction, focusing on building robust learning models and evaluation frameworks that directly impact advertising effectiveness.
Responsibilities:
• Drive modeling and data innovations for ad interaction outcome prediction under partial and noisy feedback.
• Focus on building estimated conversion models, designing data-driven attribution and weak-label generation pipelines, and developing robust learning and calibration methods for scenarios where true user outcomes are sparse, delayed, or unobservable.
• Design and evaluate multi-task and proxy-signal models, improve offline and online measurement frameworks, and translate modeling advances into production-ready systems that directly impact ad ranking, bidding, advertiser ROI, and user experience at web scale.
Qualifications:
Required:
• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
• OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• Solid programming skills in Python and at least one major ML framework (e.g., PyTorch or TensorFlow).
• Ability to independently drive modeling projects from problem definition through production and iteration.
Preferred:
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• 3+ years experience conducting research as part of a research program (in academic or industry settings).
• 1+ year(s) experience developing and deploying live production systems, as part of a product team.
• 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
• Experience working with noisy, weak, or proxy labels, including building training signals from indirect user behavior.
• Experience with conversion, outcome, or funnel modeling (e.g., post-click modeling, engagement modeling, attribution, or similar problems).
• Familiarity with model calibration, reliability analysis, or uncertainty estimation in production systems.
• Background in causal inference, attribution, or counterfactual evaluation.
• Experience with large-scale online marketplaces or ads/recommendation systems.
• Experience designing or operating multi-task / auxiliary-task learning systems.
• Proven technical leadership in cross-team modeling efforts or platform-level ML systems.
• 4+ years of industry experience building and shipping machine learning models in production.
• Solid hands-on experience with modern ML models (e.g., deep learning, tree-based models, or linear models) and feature engineering.
• Solid understanding of supervised learning and multi-task learning.
• Practical experience working with large-scale, real-world data and building end-to-end modeling pipelines (data preparation, training, validation, deployment).
• Experience with offline evaluation and online A/B experimentation for ML systems.
Company:
Microsoft provides computer software, consumer electronics, cloud computing platforms, and digital enterprise systems. Founded in 1975, the company is headquartered in Redmond, USA, with a team of 10001+ employees. The company is currently Late Stage.