Adoption Analytics & Insights Manager

appnovation; Toronto; On-site; CAD 110,000 - 190,000; Full time

Benefits offered by this job

Challenging work with real impact

Access to cutting-edge AI platforms

Diverse and inclusive culture

Growth opportunities

Collaborative environment

Exposure to high-profile projects

Supportive leadership

Hybrid working model

Job summary

Appnovation is seeking a Senior Machine Learning Engineer to lead end-to-end ML initiatives, bridging data science with engineering and business objectives. You will design scalable ML systems, apply advanced statistics, and iterate rapidly across teams to deliver measurable business impact.

The role emphasizes autonomy, architecture design for heterogeneous data, and collaboration with stakeholders to translate needs into actionable ML solutions.

Qualifications

• Bachelor's degree in Computer Science or Engineering or equivalent.
• 8–12 years of experience leading complex technical projects with multi-team impact.
• Expert capability in designing end-to-end ML systems for complex problems and advanced statistical methods.

Skills

Python

R

Pandas

NumPy

AWS Sagemaker

GCP Vertex AI

Azure ML

Spark

Docker

Education

Bachelor's degree in Computer Science or Engineering

Tools

Kubeflow

MLflow

Docker

Job description

Overview

Appnovation is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth. Bold ambition. Practical action. Endless possibilities.

About the Role

Join forces with Appnovation to deliver high-impact results for one of our key strategic partners - a global leader in their field. This engagement offers a unique vantage point into a world-class organization with exceptional opportunities for professional growth and long-term career advancement.

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results. You will bridge the gap between technical innovation and real-world business challenges by applying advanced statistical and machine learning techniques to build predictive models and derive actionable insights.

What we are looking for

• Experience & Education: Bachelor\'s degree in Computer Science or Engineering with 8-12 years of relevant experience leading complex technical projects with multi-team impact.
• Advanced ML & Statistics: Expert capability in designing end-to-end ML systems for complex problems (including imbalanced data and concept drift), applying advanced statistical methods (mixed models, survival analysis, Bayesian approaches), and demonstrating a deep understanding of causal inference techniques, experimentation design (A/B testing, MABs), and deep learning architectures for unstructured data (e.g., NLP, Computer Vision).
• Core Technology Stack: Expertise in Python (including libraries like Pandas and NumPy) or R, proficiency with cloud platforms and their data/ML services (e.g., AWS Sagemaker, GCP Vertex AI, Azure ML Services), experience with big data technologies (e.g., Spark, Hadoop), and familiarity with MLOps tools (e.g., Kubeflow, MLflow, Docker).
• Business Immersion: Proven ability to immerse in operations to acquire deep domain expertise, thinking like an insider to translate seamlessly between business needs and engineering solutions.
• Full-Stack Agility: Ability to build complete applications rapidly across any technology stack, selecting the right tools to balance technical debt with delivery speed.
• Data Strategy & Integration: Experience architecting scalable data strategies across diverse teams and complex enterprise landscapes. This includes defining data governance policies, mastering data quality frameworks, building robust integration solutions for undocumented schemas and disparate systems, and driving the adoption of modern data warehousing and lakehouse architectures.
• AI Evaluation & Governance: Experience leading AI governance initiatives, creating evaluation standards, and training teams on rigorous AI verification and risk management.
• Rapid Prototyping: Proficiency in leading rapid delivery initiatives using a prototype-first approach to validate solutions quickly before scaling.
• Problem Discovery: A track record of seeking out undefined problems, embedding with users to discover latent needs, and turning ambiguity into clear problem statements.

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model