Senior Data Scientist

The Senior Data Scientist will support the ongoing maintenance, monitoring, and improvement of production analytics and machine learning solutions offered to the clients in North America. You will ensure that models and data processes remain accurate, reliable, compliant, and aligned with business and client requirements. It focuses on operational performance, issue resolution, and continuous improvement of existing solutions.
You will report to Director of Data Science and Gen AI.
What you'll do:
Analyze, process, and document large datasets; select appropriate analytical, machine learning, and data mining techniques to identify useful insights.
Develop and maintain data structures, storage schemes, processing tools, and analytical pipelines.
Monitor model performance and stability across use cases; conduct validation, back-testing, and performance reporting.
Investigate data and model issues, identify root causes, and implement corrective actions or model updates.
Maintain documentation, version control, audit trails, and data quality practices in support of governance and compliance requirements.
Assess model outputs, conduct ROI and benefit analyses, and present findings on model performance and analytical processes, develop best practices and business assumptions that support reliable solutions and consistent model performance.
What we're looking for:
Strong grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus.
Understanding how and when to apply key analytical approaches including regression analysis, machine learning, AI, deep learning and other advanced modeling approaches to extract and automate insights from data
Strong grasp of techniques for model cross-validation and penalizing unnecessary complexity, including regularization, Bayesian shrinkage, in-sample vs out-of-sample. Fluency with statistical significance tests and Monte Carlo simulation.
Ability to write near-production-level code in at least one general purpose programming language (e.g. Python, C++).
Understanding of modern technologies in processing of large data sets, including Apache family (Hadoop, Spark), latest database technologies (e.g. Graph databases, time-series databases), and natural language processing and other tools for the parsing of unstructured data.

Employment type
Full-time

Work arrangement
Hybrid