Data Scientist

Conviva•Foster City, CA

14h•$180,000 - $230,000

About The Position

Conviva is seeking a Data Scientist with a strong foundation in machine learning and algorithms, and experience with AI-native development. The role supports Conviva’s AI initiatives and contributes to its real-time analytics platform. It is a hands-on, technically deep position for someone with a computer science or statistics background who is passionate about building scalable, intelligent systems and actively uses AI tools to accelerate their work. The Data Scientist will design and optimize machine learning solutions across statistical methods, neural networks, and deep learning for large-scale, real-time digital performance analytics. The work includes predictive modeling, anomaly detection, automated alerting, AI-driven alerts, and proof-of-concept development through production integration. The role also involves processing large-scale data with Ray and Spark, collaborating with engineering and product teams, and staying current with developments in AI and machine learning.

Requirements

PhD in Computer Science, Statistics, or a related field; alternatively, an MS with at least 3 years of applied machine learning or data science experience.
Strong foundation in traditional machine learning, including regression, classification, ensemble methods, clustering, and dimensionality reduction.
Strong foundation in deep learning and neural networks, including CNNs, RNNs/LSTMs, transformers, and attention mechanisms.
Strong foundation in statistical modeling and algorithms, including optimization, Bayesian inference, and probabilistic modeling.
Proficiency in Python, Scala, or similar languages for production-grade data science.
Demonstrated ability to take machine learning solutions from proof of concept to scalable, integrated implementation.
Habitual, productive use of AI tools such as Claude, Cursor, GitHub Copilot, or equivalent for coding, debugging, and solution design.
Ability to thrive in fast-paced, ambiguous environments and collaborate effectively across teams.

Nice To Haves

Experience with real-time data processing and streaming analytics.
Deep familiarity with time series analysis, including forecasting, change-point detection, and seasonality decomposition.
Background in building AI-powered alerting, anomaly detection, or intelligent monitoring systems.
Familiarity with cloud-based machine learning deployment and MLOps practices, including model versioning, monitoring, and retraining pipelines.
Experience fine-tuning or integrating LLMs or foundation models into analytical or product workflows.

Responsibilities

Design, build, and optimize machine learning models and solutions, including traditional statistical ML, neural networks, and deep learning, for large-scale, real-time digital performance analytics.
Develop approaches for predictive modeling, anomaly detection, and automated alerting using time series and other complex datasets.
Apply classical methods such as regression, tree-based ensembles, and clustering, as well as deep learning architectures such as transformers, LSTMs, and CNNs as appropriate.
Support AI initiatives, including designing AI-driven alerts and contributing to AI roadmaps.
Develop proof-of-concept code and implement machine learning solutions to improve product capabilities.
Use AI coding tools to accelerate prototyping, code review, and iteration.
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 and machine learning and bring innovative approaches to the team.