Tian Zhou

AI Researcher

Los Angeles, California, United States12 yrs experience

Most Likely To SwitchAI Enabled

Key Highlights

Led data science initiatives at Netflix Ads.
Developed advanced forecasting algorithms.
Expert in machine learning and data analytics.

Stackforce AI infers this person is a Data Science expert in the Advertising and Robotics industries.

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Skills

Core Skills

Data ScienceForecastingRoboticsMachine Learning

Other Skills

Data AnalyticsPredictive AnalyticsAlgorithm DesignC++MatlabSignal ProcessingJavaPattern RecognitionSQLOpenCVPythonComputer VisionDeep LearningHuman-robot InteractionReinforcement Learning

Experience

12 yrs

Total Experience

3 yrs 1 mo

Average Tenure

4 yrs

Current Experience

Netflix

3 roles

Data Science Manager

Promoted

Apr 2025 – Present · 1 yr · Los Angeles, California, United States

Lead a team of Data Scientists and Analytics Engineers to build forecasting algorithms and solutions to support sales, ops, account management, serving, and yield optimization, as part of the Netflix Ads Suite (NAS) ecosystem.
My team lead the following initiatives:
Publisher inventory and supply forecasting (eg, subscriber, engagement, seasonality etc)
Targeted inventory forecasting, covering any and all combinations of rich audience targetings
Campaign unique reach & frequency histogram forecasting
Budget reach curve forecasting for media planning and public API
Sponsorship forecasting & pricing (single title sponsorship, SOV basis etc)
Live event audience, inventory, and traffic forecasting
Contention-aware order-level max avail forecasting
Non-guarantee campaign bidding win-rate forecasting
Underwriting and revenue cannibalization prediction
Delivery risk forecasting and simulation
Sell-through rate prediction for any and all targeting segments
Ad Serving simulation modeling (eg, frequency cap effect)
Ad Serving rule validation, evaluation, and experimentation
Offline simulation to support long-term planning and upfronts
Demand Forecasting (both marco level, and also micro level with synthetic demand generation)
Revenue Forecasting for FP&A (fill rate, CPM, revenue etc)
Comprehensive forecasting analytics (eg., accuracy, robustness, monitoring, observability)
Forecasting explainability & tooling (with GenAI bots)
Forecasting platform
Forecasting to support Budget Planning
Forecasting to support VPPA and privacy checks
etc

Machine LearningForecastingData AnalyticsData Science

Staff Data Scientist

Mar 2025 – Apr 2025 · 1 mo · Los Angeles, California, United States

Tech lead to build the ads forecasting ecosystem to support ad sales, underwriting, budget planning, yield analytics, delivery risk eval, inventory management, reach forecasting, format forecasting, live forecasting, and finance forecasting.

Data AnalyticsForecastingData Science

Senior Data Scientist

Feb 2022 – Feb 2025 · 3 yrs · Los Angeles, California, United States

Aug 2023 - March 2025 (Ads DSE)
Forecasting targeted media product inventory for ad sales and ad server
Live event inventory and revenue forecasting
Feb 2022 - July 2023 (Studio Production DSE)
Forecasting resources (people, cost, facilities) for studio operation
VFX and Virtual Production resource prediction, planning, and optimization
Production schedule forecasting and launch feasibility modeling
Production Comps modeling for cost prediction, schedule planning, and vendor recommendation

Data AnalyticsForecastingData Science

Boston consulting group (bcg)

2 roles

Lead Data Scientist

Nov 2020 – Feb 2022 · 1 yr 3 mos · Los Angeles Metropolitan Area

Designed, developed, and delivered data science solutions at scale for a variety of clients ranging from Hospitality Group, Apparel Retailer, Media & Entertainment Conglomerate, Commercial & Retail Banking, Logistics Service Company, and Energy Corporation.
Specialized in advanced analytic solutions in driving top-line growth (e.g., Digital Marketing, Personalization, Advanced Recommender Systems, and Social Listening), as well as optimizing operational cost (e.g., Demand Forecasting & Labor Optimization, Predictive Maintenance, Credit Analytics, Churn Prediction, Cost Optimization, and Digital Drilling Process Optimization)
Led a team of data scientists to develop personalization engine, email campaigns, demand fore-
casting models, and labor optimization engine for a fine-dining hospitality group
Led a team of data scientists, data engineers, and UI/UX designers to develop and deploy an
end-to-end cost saving analytical engine and tool for an electronic product distributor to fully
exploit special pricing agreements with manufacturers

Data SciencePredictive Analytics

Senior Data Scientist

Sep 2018 – Nov 2020 · 2 yrs 2 mos · Los Angeles Metropolitan Area

Invented a social listening and culture trend spotting framework to capture, filter, distill, and
present trending topics in Memes, Short videos, Podcasts, and Books etc, for a leading film studio
Developed a deep neural net recommendation engine for a global fast fashion retail client and
increased the email campaign effectiveness by more than 10%
Developed spatial machine learning models to predict geologic hazards for a leading up-stream
oil & gas client, $40M projected savings and 40x speed-up in planning
Developed a cash-flow monitoring, default risk flagging, and churn prediction algorithm for a
regional US bank to better manage loan risks during COVID

Data ScienceMachine Learning

Toyota infotechnology center co., ltd.

Research Intern

Jan 2016 – May 2016 · 4 mos

Conducted research and development in the area of driver sensing and modelling, wrote patents and research papers.
Designed a context-aware hand detection algorithm for naturalistic driving conditions, which
combines Faster Region-CNN (FRCNN) with driving context such as prevalent hand shapes,
preferred driving habits and coupling effects between multiple hands.
Developed a Recurrent Neural Network (RNN) based human modelling algorithm which leverages hand activity and gaze patterns to predict maneuver and braking actions ahead of time.

Machine LearningAlgorithm Design

Purdue university

Research Assistant

Jan 2014 – Aug 2018 · 4 yrs 7 mos · West Lafayette, IN

Conducted research in the area of human robot collaboration, focusing on early turn-taking intention prediction for robotic scrub nurses
Invented multimodal surgeon workload prediction system and algorithms to accurately prediction surgeon's workload during tele-operations
Invented a hybrid surgical instrument recognition algorithm combing computer vision with robotic manipulations
Evaluated the pros and cons of various state-of-the-art touch-less sensors for robotic teleoperation's effectiveness, accuracy, ease of learning, and operator's situation awareness
Check my Google Scholar profile to find more about my publications: https://scholar.google.com/citations?user=uY4rOnkAAAAJ&hl=en

RoboticsMachine Learning