Senior Manager, Data Science

SOTIMississauga, ON
Hybrid

About The Position

SOTI is committed to providing its employees with endless possibilities; learning new things, working with the latest technologies and making a difference in the world. We are seeking a pragmatic Senior Data Science Manager to lead the development and delivery of AI-driven product capabilities that create measurable value for our customers and business. In this role, you will combine technical depth with strategic leadership, transforming data into actionable insights and scalable product features. You will collaborate closely with cross-functional teams across engineering and product to design, build, and deploy reliable AI solutions that integrate seamlessly into our platform. This position requires a hands-on leader who thrives in fast-paced product environments, prioritizing practical, real-world impact and iterative delivery over theoretical experimentation. You will also play a key role in mentoring and growing a high-performing team of data scientists and engineers, fostering a culture that balances analytical rigor with strong engineering practices.

Requirements

  • Advanced degree in computer science, data science, statistics, or a related quantitative field, or equivalent practical experience in applying AI/ML to product environments.
  • 8+ years of experience in data science, machine learning engineering, or applied AI roles, with a proven track record of shipping AI-driven features in production products.
  • 4+ years of experience managing and mentoring teams of data scientists, ML engineers, and developers in tech-driven organizations.
  • Strong hands-on programming skills in Python, SQL, and related tools, with experience building and deploying models, data pipelines, and analytical systems in cloud environments (e.g., AWS, Azure).
  • Expertise in pragmatic AI applications such as machine learning, time-series analysis, anomaly detection, user modeling, or predictive analytics, with a focus on product integration rather than research.
  • Demonstrated ability to lead combined data science and development efforts, synthesizing diverse data sources into actionable, business-impacting insights.
  • Excellent communication skills for bridging technical and non-technical audiences, including product managers, engineers, and executives.
  • Solid understanding of MLOps, scalable data architectures, and deployment patterns, with experience in monitoring and iterating on production AI systems.
  • Experience defining team standards and processes for embedding AI into products, emphasizing speed, reliability, and customer value.

Responsibilities

  • Lead the design, development, and deployment of AI and machine learning systems, including scalable pipelines for inference, analytics, and real-time processing, using modern engineering practices to ensure robustness and efficiency.
  • Collaborate with product management, development, and business teams to identify and solve product challenges through data-driven models, focusing on user behavior, predictive analytics, and operational improvements.
  • Oversee hands-on prototyping, experimentation, and iteration to validate AI solutions quickly, translating complex data insights into clear product recommendations that influence strategy and priorities.
  • Establish and enforce best practices for AI operations, including data quality, model monitoring, and cross-team collaboration to maintain high performance in production.
  • Build and mentor a high-performing team of data scientists and developers, promoting a culture of ownership, innovation, and product-oriented thinking while fostering skills in both data analysis and software engineering.
  • Partner with stakeholders to propose AI initiatives that align with business goals, driving measurable outcomes like enhanced customer experiences and optimized operations.
  • Contribute directly to code and system architecture, ensuring your team delivers production-ready solutions that leverage cloud-based tools and integrate with existing development workflows.
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