Jay (Jianqiang) Wang
12 SlideShares 137 Followers 125 Folgens
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Unternehmen/Arbeitsplatz
San Francisco Bay Area United States
Beruf
Technical Lead at Snapchat, Inc, advisor for start-ups and lead mentor in data science training
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Education
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Data scientist with 10+ years experiences in analytics and machine learning; expert knowledge and hands-on experiences in these domains: Recommender systems, evaluation metrics, explore-exploit; Ads relevance, ads click through rate prediction and ranking; Demand forecasting, discrete choice model, pricing, product portfolio management; Lead mentor in training fresh graduate students and career changers in data science; Time series modeling, nonparametric statistics, survey statistics; Counterfactual reasoning, segmentation, cohort and drill-down analysis, A/B experiment design and analysis; Data scientist tech lead in stitch fix styling algorithm team; Data scientist in twitter ads rank...
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machine learning data science data mining fashion hp online advertising boosted trees complex surveys asymptotics distance outlier detection causal inference product analytics statistics marketing retail multinomial logit models ads interview preparation analytics coding interviews twitter multinomial logit model trevor hastie discrete choice model repeated surveys agriculture dynamic linear model
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Präsentationen

(11)
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A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeated Surveys

Vor 8 Jahren • 250 Aufrufe

Multivariate outlier detection

Vor 8 Jahren • 232 Aufrufe

Multivariate outlier detection

Vor 8 Jahren • 201 Aufrufe

Boosted Tree-based Multinomial Logit Model for Aggregated Market Data

Vor 8 Jahren • 439 Aufrufe

Introduction to data science and candidate data science projects

Vor 8 Jahren • 378 Aufrufe

How to prepare for data science interviews

Vor 8 Jahren • 433 Aufrufe

Introduction to data science and its application in online advertising

Vor 8 Jahren • 484 Aufrufe

Notes on Machine Learning and Data-centric Startups

Vor 7 Jahren • 709 Aufrufe

Making data-informed decisions and building intelligent products (Chinese)

Vor 6 Jahren • 212 Aufrufe

Artificial Intelligence in fashion -- Combining Statistics and Expert Human Judgment for Better Recommendations

Vor 6 Jahren • 8 Aufrufe

The Practice of Data Driven Products in Kuaishou

Vor 2 Jahren • 117 Aufrufe

Dokumente

(1)

Boosted multinomial logit model (working manuscript)

Vor 8 Jahren • 573 Aufrufe

Gefällt mir

(3)

Real Time Analytics: Algorithms and Systems

Arun Kejariwal • Vor 7 Jahren

Deep learning: the future of recommendations

Balázs Hidasi • Vor 8 Jahren

Building a Recommendation Engine - An example of a product recommendation engine

NYC Predictive Analytics • Vor 13 Jahren
Personal Information
Unternehmen/Arbeitsplatz
San Francisco Bay Area United States
Beruf
Technical Lead at Snapchat, Inc, advisor for start-ups and lead mentor in data science training
Branche
Education
Info
Data scientist with 10+ years experiences in analytics and machine learning; expert knowledge and hands-on experiences in these domains: Recommender systems, evaluation metrics, explore-exploit; Ads relevance, ads click through rate prediction and ranking; Demand forecasting, discrete choice model, pricing, product portfolio management; Lead mentor in training fresh graduate students and career changers in data science; Time series modeling, nonparametric statistics, survey statistics; Counterfactual reasoning, segmentation, cohort and drill-down analysis, A/B experiment design and analysis; Data scientist tech lead in stitch fix styling algorithm team; Data scientist in twitter ads rank...
Tags
machine learning data science data mining fashion hp online advertising boosted trees complex surveys asymptotics distance outlier detection causal inference product analytics statistics marketing retail multinomial logit models ads interview preparation analytics coding interviews twitter multinomial logit model trevor hastie discrete choice model repeated surveys agriculture dynamic linear model
Mehr anzeigen