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Data scientist
Palitronica —Waterloo, ON
- De 100 000 $ à 125 000 $ par an
- Azure
- Recherche
- Développement logiciel
il y a 13 jours
MLOps & Data Engineer
Palitronica —Waterloo, ON
- De 90 000 $ à 120 000 $ par an
- Azure
- Dépannage de logiciel
- SQL
il y a 5 jours
Frontend / UX Engineer - Robotics Data Operations, Kitchener, ON
Siemens —Kitchener, ON
- De 85 000 $ à 130 000 $ par an
- Temps plein
- Travail hybride
- Informatique
- Ingénierie
- Maîtrise
- Régimes de participation aux bénéfices
Senior Data Scientist
Palitronica —Waterloo, ON
- De 125 000 $ à 165 000 $ par an
- Mentorat
- Python
il y a 13 jours
Principal Platform Architect – Physical AI Data & Runtime Platform, Kitchener, ON
Siemens —Kitchener, ON
- De 140 000 $ à 185 000 $ par an
- Temps plein
- Travail hybride
- Informatique
- Ingénierie
- Maîtrise
- Régimes de participation aux bénéfices
il y a 5 jours
Agentic AI & DevOps Automation Engineer - Robotics Data Platform, Kitchener, ON
Siemens —Kitchener, ON
- De 100 000 $ à 130 000 $ par an
- Temps plein
- Travail hybride
- Informatique
- Ingénierie
- Maîtrise
- Régimes de participation aux bénéfices
Senior AI/ML & Robotics Platform Engineer
Siemens —Kitchener, ON
- De 130 000 $ à 160 000 $ par an
- Temps plein
- Travail hybride
- Informatique
- Ingénierie
- Maîtrise
- Régimes de participation aux bénéfices
Engineering Manager, AI Engineering
Magnet Forensics —Waterloo, ON
- De 160 000 $ à 210 000 $ par an
- Temps plein
- Informatique
- Ingénierie
- Baccalauréat
- Congés payés
Software Developer III, ML Launchpad
Verily —Waterloo, ON
- De 120 500 $ à 136 000 $ par an
- Temps plein
- Informatique
- Java
- Baccalauréat
Lead Software Engineer - MLOps
Sun Life —Waterloo, ON
- De 90 000 $ à 140 000 $ par an
- Temps plein
- Java
- AWS
- Apprentissage automatique
Sr AI/ML Software Developer
NAVBLUE, Inc. —Waterloo, ON
- Temps plein
- Travail hybride
- Ingénierie
- Anglais
- Java
- Heures d'arrivée et de départ flexibles
- Assurance Vie
Principal Engineer - Open Source Data Platform (ODP)
Acceldata —Kitchener, ON
- De 210 000 $ à 240 000 $ par an
- Temps plein
- Doctorat
- Informatique
- Recherche
- Assurance Dentaire
- Congés payés
Lead Software Engineer - MLOps
Sun Life —Waterloo, ON
- De 90 000 $ à 140 000 $ par an
- Temps plein
- AWS
- Apprentissage automatique
- Gestion d'équipe
Sr. Manager, Technical Architect – Enterprise AI Solutions
Canadian Solar Inc. —Kitchener, ON
- Temps plein
- Azure
- Informatique
- Salesforce
- Assurance Dentaire
- Congés payés
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Data Scientist - 12 month contract
CorGTA —Toronto, ON
Education: Ph.D. or Master's degree in Computer Science, Mathematics, Statistics, or a related. Experience: 5–8 years of applied industry experience in data…
De 60 $ à 70 $ de l’heure
Data Scientist, AI Model Risk
Royal Bank of Canada —Toronto, ON
Progress towards a PhD or Master's degree in Statistics, Computer Science, Applied Mathematics, Econometrics, Engineering, Quantitative Finance, or a related…

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Data scientist

Palitronica
Waterloo, ON

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Détails du poste

Permanent
Il y a 13 jours

Compétences

Scikit-learn
Statistique
Azure
Droit
NumPy
Maintenance prédictive
Recherche
Pandas
Analyse statistique
Prise de décisions
Apprentissage profond
SciPy
Analyse et modélisation quantitatives
Développement logiciel
Science des données
Analyse statistique des données

Description complète du poste

Overview

Palitronica is seeking a Data Scientist who enjoys finding meaningful structure in complex, real-world measurement data. You will work mainly with classical and statistical machine learning, including anomaly and novelty detection, outlier analysis, clustering, classification, and data-quality assessment.

You will join an established ML system. Models are already in production, and we have a Python framework for developing, evaluating, deploying, and operating them. Your work will focus on understanding that foundation, improving model performance and robustness, and helping the system handle new data conditions and product needs.

This is not an LLM, RAG, NLP, or chatbot role. Deep learning may be considered when the data and evidence justify it, but it is not the default or the focus. Python matters because you need to understand and improve the ML framework.

Responsibilities

Explore and characterize high-dimensional physical measurement data, including quality, variability, outliers, and uncertainty.
Build strong baselines and compare statistical, supervised, semi-supervised, and unsupervised approaches.
Improve anomaly detection, outlier detection, clustering, and classification models with attention to explainability and repeatability.
Diagnose data issues and model behavior in the existing production system, including changing distributions and unexpected edge cases.
Develop useful features and representations with hardware, RF, software, and domain specialists.
Design evaluation methods for limited labels, imbalanced classes, shifting operating conditions, and false-positive trade-offs.
Read and make targeted, tested contributions to the object-oriented Python ML framework.
Partner with software and MLOps engineers on integration, reproducibility, packaging, deployment, monitoring, and traceability.
Document experiments, assumptions, results, and limitations clearly enough for others to review and reuse the work environments.

Required Qualifications

Typically, 2+ years of applied data science or machine learning experience, or equivalent substantial applied research experience.
Strong foundations in statistics, classical machine learning, experimental reasoning, and model validation.
Hands-on experience with anomaly detection, outlier or novelty detection, clustering, classification, or closely related methods.
Proficiency with Python and common scientific-computing tools such as NumPy, pandas, SciPy, and scikit-learn.
Ability to navigate modular production code, contribute testable changes, and participate constructively in code review.
Sound judgment about leakage, class imbalance, threshold selection, uncertainty, and performance trade-offs.
Clear communication and the ability to work across data science, engineering, and hardware disciplines

Nice to Have

Sensor, time-series, spectral, RF, industrial, or scientific measurement data.
Signal processing, experimental design, weak supervision, or learning with sparse labels.
Distribution shift, experiment tracking, model monitoring, or Azure-based ML workflows.
Manufacturing, test and measurement, quality assurance, predictive maintenance, or cyber-physical systems.

Export Control, Controlled Goods & Security Eligibility

This position requires direct or indirect access to hardware, software, or technical information controlled under the Canadian Export Control List, the Canadian Controlled Goods Program, the Canadian Industrial Security Program, the U.S. International Traffic in Arms Regulations (ITAR), and/or the U.S. Export Administration Regulations (EAR).
All applicants must be eligible or able to obtain authorization for such access, including eligibility for the Canadian Controlled Goods Program, and must be able to obtain a Canadian NATO Secret clearance.

Why Join Palitronica?

Work with cutting-edge technology at the intersection of cybersecurity, AI, and advanced electronics testing.
Help protect critical supply chains and infrastructure.
Join a high-growth company serving some of the world's most demanding industries.
Collaborate with a talented and mission-driven team.
Make a measurable impact on the company's growth trajectory.
Palitronica is an equal opportunity employer and welcomes applications from all qualified candidates.

Use of AI in Hiring

Palitronica may use artificial intelligence tools to assist with the screening or assessment of applicants. These tools are used strictly as an aid, and all hiring decisions are made by human reviewers.

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mlops & data emplois - cambridge, on

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Je souhaite recevoir la dernière alerte emploi pour les postes de ce type : mlops & data (cambridge, on)

Overview

Responsibilities

Required Qualifications

Nice to Have

Export Control, Controlled Goods & Security Eligibility

Why Join Palitronica?

Use of AI in Hiring

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