Senior Data Scientist

ConvivaFoster City, CA

About The Position

Conviva is seeking a Senior Data Scientist with a strong foundation in Machine Learning, Algorithms, and experienced with AI-native development to help drive AI Initiatives and contribute to the development of their 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 actively leverage AI tools to accelerate their work. The role involves designing, building, and optimizing ML models and solutions, developing innovative approaches for predictive modeling, anomaly detection, and automated alerting, and applying a wide spectrum of algorithms. The Senior Data Scientist will support AI initiatives, develop POC code, implement ML solutions, process and analyze large-scale data, and collaborate with cross-functional teams. Staying current with industry trends in AI/ML and bringing innovative approaches to the team is also a key aspect of the role.

Requirements

  • 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.
  • Strong foundation in Deep Learning & Neural Networks: CNNs, RNNs/LSTMs, Transformers, attention mechanisms.
  • Strong foundation in 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.

Nice To Haves

  • 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.

Responsibilities

  • 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.

Benefits

  • equity
  • benefits
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