Senior Data Scientist (Canada)

Atreides Caseri Inc.

2d • Hybrid

About The Position

As a Senior Data Scientist at Atreides, you will lead deep analytical investigations that uncover structure, relationships, and operational insight from complex and high-volume data streams. You’ll architect workflows for pattern identification, anomaly detection, and interaction analysis across disparate data sources — often involving tracked entities, sensor feeds, or behavioral signals. You will also define and implement quality assurance methodologies that ensure analytical outputs are consistent and in terpretable, collaborating closely with engineers to embed those checks in production systems. In addition, you’ll take point on high-value or urgent analytic requests from internal and external stakeholders, helping translate open-ended questions into reliable, data-driven answers.

Requirements

• 5+ years of experience in data science, applied analytics, machine learning, or analytical R&D.
• Advanced expertise in Python and distributed compute frameworks (e.g., Spark, Databricks), including strong proficiency in Spark SQL .
• Strong background in statistical inference, anomaly detection, clustering, interaction modeling , or other analytical methods suited to large and heterogeneous datasets.
• Experience working with multi-source, semi-structured, geospatial, or entity-centric data , with a strong ability to derive insight from complex operational environments.
• Demonstrated success building data quality, validation, or reliability frameworks , particularly for analytical workflows or model-adjacent processes.
• Ability to translate ambiguous analytical problems into structured, reproducible investigation plans.
• Excellent communication, mentorship, and cross-functional collaboration skills.

Nice To Haves

• Experience with MLflow , feature stores, or MLOps platforms; familiarity with model lifecycle management, reproducibility tooling, or production model monitoring.

Responsibilities

• Design and lead investigations into patterns, trends, and edge cases across filtered datasets.
• Develop interaction models and fused analyses across multiple entity types and data modalities.
• Design data validation, anomaly sanity checks, and analytical reliability frameworks to ensure analytical outputs behave correctly across v aried data inputs.
• Partner with solutions and data engineering to embed analytic logic into data pipelines and services.
• Conduct bespoke, high-complexity analysis in support of customer-facing or operational needs.
• Guide team best practices in Spark SQL usage, data documentation, and exploratory reproducibility.

Benefits

• Competitive salary
• Comprehensive health, dental, and vision insurance plans
• Flexible hybrid work environment
• Additional benefits like flexible hours, work travel opportunities, competitive vacation time and parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed