Senior Data Scientist - ML & Algorithms Focus

Conviva•Foster City, CA

40d•$170,000 - $200,000

About The Position

Conviva is the intelligence layer for digital businesses, turning every consumer interaction into outcome-based intelligence-linking engagement patterns across AI agents, apps, websites, and streaming video to real results such as purchases, bookings, and resolved support requests. Powered by its patented Time-State Technology, the Conviva Operational Data Platform delivers real-time insights and automation that help leading enterprises grow, improve satisfaction, and build lasting trust. We are looking for a Data Scientist with strong foundation in Machine Learning and Algorithms to help drive our AI Initiatives and contribute to the development of our Real-Time Performance Analytics Platform. This is a hands-on, technically deep role ideal for individuals with a background in Computer Science or Statistics and a passion for building scalable, intelligent systems. You'll work on developing and deploying advanced ML models - including predictive modeling, anomaly detection, and time series forecasting within a high-performance, production-grade environment.

Requirements

PhD in Computer Science, Statistics or a related technical field; or MS in Computer Science/Statistics with 3+ years of experience in applied ML or data science roles.
Strong foundation in machine learning, statistical modeling, and algorithms with experience in predictive modeling and data analysis.
Proficiency in coding and programming for data science applications (e.g., Python, Scala, or similar languages)
Ability to develop POC code and implement ML models into scalable solutions.
Thrive in fast-pace, ambiguous environments and effectively collaborate across teams.

Nice To Haves

Experience with real-time data processing and analytics.
Familiarity with time series analysis and forecasting techniques.
Background in building AI-powered alerts, anomaly detection, or similar AI driven applications.
Familiarity with cloud-based ML deployment and MLOps best practices.

Responsibilities

Design, build and optimize machine learning models and solutions to solve real-world problems in large-scale real-time digital performance analytics.
Develop innovative approaches for predictive modeling, anomaly detection, and automating alerting using time series and other complex datasets.
Support AI initiatives, including designing AI-driven alerts and contributing to AI roadmaps.
Work with time series data and other complex datasets to develop predictive and anomaly detection models.
Develop proof-of-concept (POC) code and implement ML solutions that improve product capabilities.
Process and analyze large-scale data using Ray and Spark.
Collaborate with cross-functional teams, including engineering and product teams, to integrate models into production systems.
Stay up to date with industry trends in AI, machine learning, and data science to bring innovative ideas to the team.