priya.v@netflix.com+1 310 555 0456Los Gatos, CAlinkedin.com/in/priyavenkatesh-data
Professional Summary
Data science leader with 13 years building recommendation systems, experimentation platforms, and ML infrastructure at Netflix, Spotify, and LinkedIn. Managed 35 data scientists and ML engineers. At each company delivered multiple concurrent ML products. 8 papers in KDD, RecSys, NeurIPS.Skills
Python, R, SQL, TensorFlow, PyTorch, Spark, Airflow, Kubeflow, Recommendation Systems, Causal Inference, A/B Testing, NLP, ML Infrastructure, Experimentation, Bayesian Stats, Team LeadershipCertifications
Google Cloud Professional ML Engineer
Stanford Statistical Learning
Awards
Netflix Data Science Impact Award — Netflix · 2023
Spotify Hack Week Winner — Spotify · 2016
Languages
English (Native), Hindi (Native), Tamil (Fluent), Spanish (Basic)Interests
ML fairness, open-source RecSys, mentoring PhD studentsExperience
Head of Data Science
Netflix · Los Gatos, CA
• Project: Content Valuation — Saved $400M+ annual content spend
• Project: Experimentation Platform — 1,000+ concurrent A/B tests
• Project: Play Something — 15M+ weekly completions via contextual bandits
• Project: Model Monitoring — Drift incidents −72%
• Lead 35-person org across RecSys, Content Analytics, Growth
• Owned metrics layer covering 63 KPIs with clear ownership
• Designed experiments lifting primary metric 20%
Senior Data Science Manager
Netflix · Los Gatos, CA
• Project: Cold-Start Recs — D30 retention +11% for new subscribers
• Project: Metadata Enrichment — 100K+ titles/day pipeline
• Built RecSys team of 12 engineers
• Designed experiments lifting primary metric 8%
• Owned metrics layer covering 94 KPIs with clear ownership
• Improved data quality; critical incidents down 64%
Data Science Manager
Spotify · New York, NY
• Project: Podcast Recs — Launched to 100M+ users
• Project: Causal Playlist Framework — First firm-wide causal inference toolkit
• Led Discover Weekly team of 8
• Reduced reporting latency from days to hours for 9 stakeholder teams
• Designed experiments lifting primary metric 21%
• Owned metrics layer covering 45 KPIs with clear ownership
Senior Data Scientist
LinkedIn · Sunnyvale, CA
• Project: Skills Taxonomy NLP — 1M+ skill entities
• Project: Real-Time Feature Store — Sub-10ms serving
• Published 3 papers at KDD and RecSys
• Built models/pipelines at LinkedIn impacting $2M+ decisions annually
• Reduced reporting latency from days to hours for 10 stakeholder teams
• Designed experiments lifting primary metric 16%
Data Scientist
Amazon · Seattle, WA
• Project: Recs A/B Framework — Experimentation for recs engine
• Project: Fresh Forecasting — Forecast accuracy +12%
• Documented analysis playbooks used across the org
• Built models/pipelines at Amazon impacting $6M+ decisions annually
• Reduced reporting latency from days to hours for 11 stakeholder teams
• Designed experiments lifting primary metric 11%
BI Analyst
QueryForge · Toronto, Canada
• Improved data quality; critical incidents down 33%
• Partnered with eng to productionize 5 ML/analytics products
• Created self-serve dashboards adopted by 93+ users
• Documented analysis playbooks used across the org
• Built models/pipelines at QueryForge impacting $4M+ decisions annually
• Reduced reporting latency from days to hours for 12 stakeholder teams
• Designed experiments lifting primary metric 18%
BI Analyst
Metric Labs · Toronto, Canada
• Built models/pipelines at Metric Labs impacting $7M+ decisions annually
• Reduced reporting latency from days to hours for 7 stakeholder teams
• Designed experiments lifting primary metric 21%
• Owned metrics layer covering 83 KPIs with clear ownership