About KenWave

KenWave Solutions Inc. is transforming the way critical infrastructure is inspected and managed. Our patented Agile Response Imaging™ (DRI™) technology combines vibroacoustic sensing, advanced signal processing, data analytics, and machine learning to assess the condition of pressurized pipelines without taking them out of service.

As part of Obayashi, KenWave is building the next generation of infrastructure intelligence platforms for water, industrial, and energy pipeline owners worldwide.

The Opportunity

We are seeking a Principal Data Scientist to lead the development of advanced analytics, machine learning, signal processing, and AI capabilities that form the foundation of KenWave's technology roadmap.

This is a rare opportunity to work at the intersection of: Physics

Acoustics and vibration

Machine learning

Digital twins

Infrastructure intelligence

Signal processing

Large-scale data analytics The successful candidate will be the senior technical authority for data science and analytical algorithms, helping transform KenWave from a project-based analytics organization into a scalable technology platform company.

Key Responsibilities Technical Leadership 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.

Technical

Governance & Methodology Oversight Serve as the technical owner and final technical authority for KenWave’s production analytical methods, algorithms, statistical and machine learning models,



and associated validation methodologies.

Establish technical standards, design principles, development practices, and acceptance criteria for the Data Science, Algorithms and Analytics function

Review and approve changes to production analytical methodologies and algorithms prior to release Signal Processing & Advanced Analytics Develop and enhance algorithms for:

Vibroacoustic analysis

Spectral analysis

Modal analysis

Time-frequency analysis

Structural response characterization

Anomaly detection

Design robust feature extraction frameworks from field-collected waveforms.

Improve pipeline condition assessment accuracy and repeatability.

Design and configure robust metadata tracing and analytics output standards

Design and develop distributable software within scalable environments Machine Learning & AI Lead development of machine learning models supporting:

Condition classification

Pipe deterioration assessment

Leak detection

Predictive infrastructure maintenance

Risk scoring

Evaluate modern AI approaches including:

Deep learning

Physics-informed machine learning

Bayesian models

Foundation models

Agent-based analytics

Establish reproducibility, traceability, version control, documentation, and testing standards for production algorithms and models Product and Commercialization Work closely with Product, Engineering, Operations,



and Executive teams.

Translate research concepts into deployable customer-facing capabilities.

Support the transition toward automated and AI-assisted condition assessment.

Contribute to patent development and intellectual property creation. Research and Innovation Universities

Research organizations

Industry partners

Government-funded programs

Publish technical papers and support conference presentations.

Identify emerging technologies that may create competitive advantage.

Required Qualifications

Education: Data Science

Computer Science

Engineering

Applied Mathematics

Physics

Signal Processing

Vibro-Acoustics

Related quantitative discipline

PhD or Master's degree in one of: Experience 10+ years in advanced analytics, machine learning, or computational research.

Experience leading high-impact technical projects.

Experience mentoring and developing technical teams.

Technical

Skills

Strong experience in: Python

Machine Learning

Statistical Modelling

Signal Processing

Time-Series Analysis Experience with: Scikit-Learn

PyTorch

Git/GitHub

Cloud Platforms (AWS/Azure)

Data Engineering Pipelines

MLOps Strong understanding of: SQL

Experimental design

Statistical inference

Optimization

Algorithm development Preferred Qualifications The following are considered significant assets: Vibroacoustics

Acoustics & vibration engineering

Pipeline assessment

Non-destructive testing (NDT)

Utilities infrastructure

Water industry

Oil & gas pipeline monitoring

Finite Element Analysis (FEA)

Physics-informed machine learning

Digital twins

Geospatial analytics

This is a non-management position

📌 Principal Data Scientist (Mississauga)
🏢 KenWave Solutions
📍 Mississauga