CLDRSRC10411 - Data Analytical Specialist/Scientist - Toronto - Hybrid

Indotronix UK; Toronto; Híbrido; CAD 90 000 - 130 000; Tempo integral

Resumo da oferta

Cloud Resourcing is seeking a Data Analytical Specialist/Scientist for a hybrid role in Toronto, ON. The candidate will leverage deep statistical knowledge and hands-on ML with Python/SQL to build, validate and tune models on real-world datasets, using tools like Power BI, Databricks, and Azure Foundry.

The ideal candidate has extensive experience (10–15 years) and will work in a hybrid setup to deliver data-driven insights and scalable analytics solutions.

Qualificações

• Deep expertise in statistics, probability, predictive modelling and machine learning including classification, regression, clustering, feature engineering, experimentation, model selection, validation, bias/variance, overfitting and inference.
• Advanced hands-on proficiency in Python, SQL and ML frameworks, with demonstrated experience building, tuning and validating models using real-world datasets. Tech stack: Python, SQL, Power BI, VSCode, Git, Jira, Azure (OpenAI, Foundry and ML Studio), Databricks.
• Strong hands-on experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry.

Responsabilidades

• Develop and validate predictive models on real-world datasets.
• Tune and validate models using experimentation and real-world data.
• Create data visualizations and dashboards (Power BI) to communicate insights.
• Collaborate with cross-functional teams in Azure ecosystem.

Conhecimentos

Statistics/ML concepts

Python & SQL

Azure ML Foundry

Ferramentas

Python

SQL

Power BI

VSCode

Git

Jira

Azure AI Foundry

Databricks

Descrição da oferta de emprego

CLDRSRC10411 - CLDRSRC10411 - Data Analytical Specialist/Scientist - Toronto - Hybrid

[Toronto, ON, M5A 3N7], Canada

10 - 15 Years

N/A

Posted 2 days ago

About Company

Cloud Resourcing is IT focused recruitement firm with focus on finding the bext role for the qualified candidates. We are seeking qualified resource for the following:

Job Description

Must Haves:

• Deep expertise in statistics, probability, predictive modelling and machine learning, including classification, regression, clustering, feature engineering, experimentation, model selection, validation, bias/variance, overfitting and statistical inference.
• Advanced hands-on proficiency in Python, SQL and ML frameworks, with demonstrated experience building, tuning and validating models using real-world datasets. Tech stack: Python, SQL, Power BI, VSCode, Git, Jira, Azure (OpenAI, Foundry and ML Studio), Databricks.
• Strong hands-on experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry, includin...