Senior Data Scientist – Infrastructure Analytics & AI

KenWave Solutions; Mississauga; On-site; CAD 120,000 - 180,000; Full time

Job summary

KenWave Solutions Inc. seeks a Principal Data Scientist to lead advanced analytics, ML, signal processing, and AI across the DRI platform. You will drive the data science strategy and establish scalable analytics foundations for infrastructure intelligence.

Lead and mentor teams, govern production analytics methodologies, and collaborate with product and engineering to translate research into deployable capabilities across water, industrial, and energy pipelines.

Qualifications

• PhD or Master’s degree in a quantitative field is required.
• 10+ years in advanced analytics, machine learning, or computational research.
• Experience leading high-impact technical projects.
• Experience mentoring and developing technical teams.
• Strong capabilities in Python, ML, signal processing, and time-series analysis.

Responsibilities

• Define and execute KenWave's data science and AI strategy.
• Establish long-term analytics and machine learning roadmaps.
• Lead the design of next-generation DRI analytical methods.
• Guide architecture decisions for analytics and AI components within the DRI platform.
• Mentor Data Scientists, Data Analysts, and Data Engineers.
• Serve as the technical owner of production analytics methods and models.

Skills

Python

Machine Learning

Signal Processing

Time-Series Analysis

Vibroacoustics

Statistical Modelling

Scikit-Learn

PyTorch

Git/GitHub

Cloud Platforms (AWS/Azure)

MLOps

Education

PhD or Master’s in a quantitative field

Tools

Scikit-Learn

PyTorch

Git/GitHub

Cloud Platforms (AWS/Azure)

Data Engineering Pipelines

MLOps

Job description

KenWave Solutions Inc. seeks a Principal Data Scientist to lead advanced analytics, ML, signal processing, and AI across the DRI platform. You will drive the data science strategy and establish scalable analytics foundations for infrastructure intelligence.

Lead and mentor teams, govern production analytics methodologies, and collaborate with product and engineering to translate research into deployable capabilities across water, industrial, and energy pipelines.