Job description

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

Requirements

Must-haves

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.
PhD in Computer Science, Statistics, or related field; or MS with 5+ years of applied ML/data science experience.
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.
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.
Learn more at conviva.ai and follow the company on LinkedIn and YouTube .

Nice-to-haves

What Would Make You Stand Out (Bonus Points):

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpython

Platform: greenhouse
Effort: quick