Senior Data Scientist (IoT)

TL;DR

Senior Data Scientist (IoT/SaaS): Building and optimizing data pipelines and analytics models for the Emissions application with an accent on device health insights and scalable data architecture. Focus on operationalizing ML models, designing production-grade data solutions, and leveraging AI to improve productivity.

Location: Must be based in Ontario, Canada. Hybrid options available in London and Kitchener, or fully remote within Ontario. No relocation assistance provided.

Salary: $100,000–$115,000 per year

Company

hirify.global is a leading IoT SaaS platform connecting machines, people, and systems in the global construction industry.

What you will do

• Design, build, and maintain scalable data pipelines and models for device health insights.
• Operationalize analytics models and algorithms into robust, production-grade data solutions.
• Improve and scale data pipeline architecture to meet evolving business and customer needs.
• Collaborate with Product and Engineering Managers on technical design and system architecture.
• Mentor other data engineers and contribute to engineering culture through code reviews.
• Showcase work and gather input through regular demos and knowledge-sharing sessions.

Requirements

• Degree in Engineering, Computer Science, or a similar technical field.
• Strong background in data engineering, data warehousing, or AI/ML.
• Hands-on experience with the Databricks platform and its ecosystem.
• Proficiency in Python, SQL, and Spark for real-world data scenarios.
• Experience using Git/GitHub and CI/CD in cloud environments.
• Must be located in Ontario, Canada.

Nice to have

• Strong motivation to leverage AI to improve efficiency and productivity.
• Active interest in exploring new technologies, programming languages, and frameworks.

Culture & Benefits

• Agile growth SaaS environment with opportunities for internal career progression.
• International work environment with regular check-ins and social events.
• Commitment to professional development through training, coaching, and open feedback.
• Flexible hybrid work setup with provided IT equipment.
• Inclusive workplace focused on diversity, equity, and inclusion (TIDE).

Hiring process

• Initial phone screen with the People & Talent team.
• Virtual meet and greet with the Engineering Manager and team.
• Assignment-specific interview featuring a case study presentation.
• Final virtual or in-person interview.