--- title: 'Senior Data Scientist at Conviva' canonical: 'https://feeny.ai/job/senior-data-scientist-conviva-foster-city-d2z8vr7xh2p2' type: 'job' last_seen: '2026-09-09' --- # Senior Data Scientist at Conviva - **Company:** Conviva - **Location:** Foster City, CA - **Posted:** 2026-06-30 - **Last confirmed live:** 2026-09-09 - **Apply:** https://www.conviva.ai/careers/job/7789435003?gh_jid=7789435003 ## Job description Conviva is the first and best place to understand and optimize digital customer experiences. Our Operational Data Platform harnesses full-census, comprehensive client-side telemetry—capturing every aspect of customer experience and engagement across all devices and linking them to the performance of underlying services, in real-time and at a fraction of the cost of alternative solutions. Conviva computes quality of experience across all users and all devices, in real time. We combine user actions with app and system responses to give your technology, business, and operations teams AI-powered insights into any issues impacting user experience and engagement. Trusted by industry leaders like Disney, NBC, and the NFL, Conviva revolutionizes how businesses understand customer experience and engagement, maximizing satisfaction, conversion, and revenue. We are looking for a Senior Data Scientist with a strong foundation in Machine Learning, Algorithms, and experienced with AI-native development to help drive our AI Initiatives and contribute to the development of our Real-Time Analytics Platform. This is a hands-on, technically deep role ideal for individuals with a background in Computer Science or Statistics who are passionate about building scalable, intelligent systems — and who actively leverage AI tools to accelerate their work. What Success Will Look Like: - Design, build, and optimize ML models and solutions — spanning traditional statistical ML, neural networks, and deep learning — to solve real-world problems in large-scale, real-time digital performance analytics. - Develop innovative approaches for predictive modeling, anomaly detection, and automated alerting using time series and other complex datasets. - Apply the full algorithm spectrum: from classical methods (regression, tree-based ensembles, clustering) to advanced deep learning architectures (transformers, LSTMs, CNNs) as the problem demands. - Support AI initiatives including designing AI-driven alerts and contributing to AI roadmaps. - Develop POC code and implement ML solutions that improve product capabilities — using AI coding tools (e.g., Claude, Cursor) natively to accelerate prototyping, code review, and iteration cycles. - Process and analyze large-scale data using Ray and Spark. - Collaborate with cross-functional engineering and product teams to integrate models into production systems. - Stay current with industry trends in AI/ML and bring innovative approaches to the team. Who You Are and What You've Done: - PhD in Computer Science, Statistics, or related field; or MS with 5+ years of applied ML/data science experience. Strong foundation in: - Traditional ML: regression, classification, ensemble methods, clustering, dimensionality reduction - Deep Learning & Neural Networks: CNNs, RNNs/LSTMs, Transformers, attention mechanisms - Statistical modeling & algorithms: optimization, Bayesian inference, probabilistic modeling - Proficiency in Python (primary), Scala, or similar languages for production-grade data science. - Demonstrated ability to ship — from POC to scalable, integrated ML solution. - AI-native developer: actively uses AI tools (Claude, Cursor, GitHub Copilot, or equivalent) in daily workflow for coding, debugging, and solution design — not just awareness, but habitual, productive use. - Thrives in fast-paced, ambiguous environments and collaborates effectively across teams. What Would Make You Stand Out (Bonus Points): - Experience with real-time data processing and streaming analytics. - Deep familiarity with time series analysis — forecasting, change-point detection, seasonality decomposition. - Background in building AI-powered alerting, anomaly detection, or intelligent monitoring systems. - Familiarity with cloud-based ML deployment and MLOps practices (model versioning, monitoring, retraining pipelines). - Experience fine-tuning or integrating LLMs/foundation models into analytical or product workflows. The expected salary range for this full-time position is $180,000 - $230,000 + equity + benefits. Compensation is determined by numerous factors such as your qualifications, experience, relevant education or training, and work location. To learn more about how Conviva can help improve the performance and outcomes of your digital services, visit [www.conviva.ai.](https://www.conviva.ai/) ## About Conviva ## Company Overview - **One-liner**: Conviva is a consumer-perspective analytics platform for the agentic era, using full-census client-side telemetry to provide real-time insights into digital experiences across apps, websites, and AI agents. - **Entity Type**: Private (Privately Held) — $110M total funding across 7 rounds - **Headquarters**: Foster City, California, United States - **Founded**: 2006 - **Founders**: Dr. Hui Zhang, Dr. Ion Stoica, Aditya Ganjam, Jibin Zhan ## Core Business - **Primary industry**: Digital Experience Monitoring (DEM), analytics, and software development - **Target customers**: B2B — streaming platforms, media companies, and any organization running consumer-facing digital products (apps, websites, AI agents) - **Mission**: "Reimagining consumer-perspective analytics" — turning every digital interaction into outcome-based intelligence that reveals how experiences truly perform and drive results ## Products & Services - **Conviva Platform (Consumer-Perspective Analytics)**: A SaaS analytics platform that ingests full-census client-side telemetry (sensors on 99% of devices) and uses a patented stateful analytics engine to continuously analyze every session and conversation. It exposes behavioral patterns, connects them to business outcomes, and surfaces opportunities for improvement in real time. Supports apps, websites, and AI agents. - **Digital Product Insights**: A new offering built for the agentic era, providing experience analytics for apps, websites, and AI agents — measuring outcomes, friction, and risk once AI is deployed in production. - **Time-State Data Platform**: Conviva’s underlying data platform that enables explainable, real-time analysis of complex systems (originally built for video QoE, now extended to agentic AI). ## Market Standing - **Valuation/Market Cap**: Not disclosed - **Key Metric**: Total Funding of **$110M** (as of latest round) - **Notable Investors/Partners**: Foundation Capital, Kalaari Capital, Notable Capital; also backed by multiple venture rounds and corporate investors. Partners include major streaming platforms (Fox, Peacock). - **Growth Signals**: - 267 employees (+4.8% YoY) operating across 12 countries including India, China, UK, Spain, Brazil - Named a **Leader in Digital Analytics by G2 Winter 2026** - Recognized as a **Visionary in the 2025 Gartner® Magic Quadrant™ for Digital Experience Monitoring** - Processes **5 trillion+ events/day** with **12 billion+ metric computations/minute** - 7 billion+ sensors deployed on devices ## Competitive Advantages - **Full-census, client-side telemetry** (not sampling) — every interaction is captured, providing a complete view of consumer experience - **Patented stateful analytics engine** that connects behavioral patterns to outcomes in real time - **Unmatched scale**: 99% sensor coverage on devices, handling trillions of events daily - **Agentic AI readiness**: Extending its analytics to measure the behavior, efficiency, and failure modes of AI agents in production — a frontier few competitors address - **Industry-first achievement**: Only intelligence layer that links consumer engagement patterns to business outcomes at any scale ## Strategic Focus - **Expanding from video experience analytics into agent experience analytics** — measuring how effectively AI agents reach outcomes, how much friction they introduce, and where breakdowns occur across real customer interactions - **Reducing data warehouse costs** by providing actionable intelligence that lowers the need for massive raw data storage - **Improving MTTD (Mean Time to Detection)** and overall customer satisfaction for digital products ## Why Work Here - **Culture highlights**: Values include "growth mindset," "ownership & urgency," "curiosity & desire to learn," "positive energy & intent," "eagerness to understand & solve customer problems," and "instinct to act & help." Emphasis on collaboration, accountability, and innovation. - **Remote/hybrid/office policy**: Offices in **Silicon Valley (Foster City, CA)**, **Bengaluru, India**, and **Beijing, China**. The Bengaluru office features a "work-from-anywhere atmosphere" with active communal spaces and quiet zones; the Foster City HQ is an open workspace with sweeping views. Not explicitly remote-first, but flexible work environment is described. - **Notable perks**: - Daily catered lunches, snacks, and beverages - Gym & shower facilities, bike storage, outdoor courtyard - EV charging stations - Shuttle service to Hillsdale Caltrain Station (Foster City) - Health insurance, wellness programs, retirement plans (varies by region) - Career coaching, internal leadership development, funding for personal/professional development - Corporate social responsibility: volunteer time off, donation matching - Inclusivity & belonging initiatives, cultural celebrations - **Engineering culture**: Innovation-driven, working on big data streaming, real-time analytics, and AI agent measurement. Teams are technical (146 people in technical roles), with alumni going to Google, Amazon, Apple, Roku, etc. Talent sourced from top tech companies (Amazon, Google, New Relic, Akamai). ## Sources 1. [conviva.ai](https://www.conviva.ai/) 2. [conviva.ai/careers](https://www.conviva.ai/careers/) 3. [conviva.ai/conviva-leadership](https://www.conviva.ai/conviva-leadership/) 4. [linkedin.com/company/conviva](https://www.linkedin.com/company/conviva) 5. 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