Data Scientist

Conviva
Foster City, CA
On-site

Who this role is best for

Best suited to technically proficient data scientists with AI-native development experience working in real-time analytics and streaming domains.

Best fit for

  • Candidates with advanced degrees and hands-on ML deployment experience in real-time analytics platforms
    — “PhD in Computer Science, Statistics, or related field; or MS with 3+ years of applied ML/data science experience.”
  • Individuals who use AI coding tools habitually and effectively for daily development tasks
    — “AI-native developer: actively uses AI tools (Claude, Cursor, GitHub Copilot, or equivalent) in daily workflow for coding, debugging, and solution design”
  • Candidates with a proven track record of moving ML prototypes into production systems
    — “Demonstrated ability to ship — from POC to scalable, integrated ML solution.”

Things to consider

  • The role requires a strong commitment to real-time data processing and analytics systems
    — “Process and analyze large-scale data using Ray and Spark.”
  • Geographic location may impact eligibility for compensation and equity package
    — “The expected salary range for this full-time position is $180,000 - $230,000 + equity + benefits.”

How to stand out

  • Highlight experience with time series analysis and anomaly detection in your resume and interview responses
    — “Develop innovative approaches for predictive modeling, anomaly detection, and automated alerting using time series and other complex datasets.”
  • Demonstrate your ability to integrate models into production systems through specific case studies
    — “Collaborate with cross-functional engineering and product teams to integrate models into production systems.”
  • Showcase your use of AI-native tools in your coding projects and workflows
    — “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.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developing ML models for real-time analytics
  • Improving product capabilities with AI
Typical background
PhD or MS in Computer Science or Statistics3+ years of applied ML/data science experience

Skills & requirements

Required

Machine LearningDeep LearningTime Series AnalysisReal-time AnalyticsAi-native Development

Preferred

LLM IntegrationCloud-based ML Deployment

Stack & domain

Machine LearningAlgorithmsAi-native DevelopmentReal-time Data ProcessingStreaming AnalyticsTime Series AnalysisForecastingChange-point DetectionSeasonality DecompositionAi-powered AlertingAnomaly DetectionIntelligent Monitoring SystemsCloud-based ML DeploymentMlops PracticesModel VersioningMonitoringRetraining PipelinesLlms/foundation ModelsRaySparkProblem-solvingCommunicationTeamworkCollaborationAIMLData ScienceReal-time AnalyticsStreaming VideoDigital Performance Analytics

About the role

Original posting from Conviva via Greenhouse

Conviva is the experience analytics platform for AI agents, apps, and streaming. Conviva pioneered quality of experience measurement for streaming video and has supported live digital experiences across 20 Super Bowls, 10 Olympic Games, and five FIFA World Cup tournaments. With full-census, real-time, stateful analytics, Conviva shows what consumers actually experience, not just whether systems are running, and connects that experience to revenue, retention, and risk.

We are looking for a Data Scientist with a strong foundation in Machine Learning, Algorithms, and experience 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 3+ 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.

Learn more at conviva.ai and follow the company on LinkedIn and YouTube.

Source: Conviva careers (Greenhouse)

Similar roles

More roles at Conviva