Senior Data Scientist

Conviva•Toronto, ON

2d•$180,000 - $230,000

About The Position

Conviva is seeking a Senior Data Scientist to advance AI initiatives and contribute to its real-time analytics platform. This hands-on, technically deep role focuses on building scalable, intelligent systems for large-scale, real-time digital performance analytics. The position is suited to someone with a background in computer science or statistics who actively uses AI tools to accelerate development. The role spans statistical machine learning, neural networks, and deep learning, including predictive modeling, anomaly detection, automated alerting, and other solutions for complex datasets. The Senior Data Scientist will develop proof-of-concept code and production-integrated ML solutions, process large-scale data with Ray and Spark, and work with engineering and product teams to integrate models into production. The position also supports AI-driven alerts and AI roadmaps, while keeping current with advances in AI and machine learning. The expected salary range for this full-time position is $180,000–$230,000, plus equity and benefits. Compensation depends on factors including qualifications, experience, relevant education or training, and work location.

Requirements

PhD in Computer Science, Statistics, or a related field, or a master's degree with 5+ years of applied machine learning or data science experience.
Strong foundation in traditional machine learning, including regression, classification, ensemble methods, clustering, and dimensionality reduction.
Knowledge of deep learning and neural networks, including CNNs, RNNs/LSTMs, transformers, and attention mechanisms.
Knowledge of statistical modeling and algorithms, including optimization, Bayesian inference, and probabilistic modeling.
Proficiency in Python (the primary language), Scala, or a similar language for production-grade data science.
Demonstrated ability to take machine learning solutions from proof of concept through scalable production integration.
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 building AI-powered alerting, anomaly detection, or intelligent monitoring systems.
Familiarity with cloud-based ML 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 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 algorithms such as regression, tree-based ensembles, and clustering, as well as deep learning architectures such as transformers, LSTMs, and CNNs, as appropriate to the problem.
Support AI initiatives, including designing AI-driven alerts and contributing to AI roadmaps.
Develop proof-of-concept code and implement ML solutions that improve product capabilities, using AI coding tools to accelerate prototyping, code review, and iteration.
Process and analyze large-scale data using Ray and Spark.
Collaborate with engineering and product teams to integrate models into production systems.
Stay current with AI/ML industry trends and bring innovative approaches to the team.