Azure Data Scientist
2 weeks ago
Position Name – Azure Data Scientist (Databricks & Python)
Type of hiring – Fulltime/Subcon
Location – Brampton, ON (4 days a week onsite & 100% onsite from Feb' 2026)
Need 9+ Years of overall experience
Job Description:
We are looking for an experienced
Azure Data Scientist
with strong skills in
Databricks
and
Python
to design, build, and deploy advanced analytics and machine learning solutions on Microsoft Azure. The ideal candidate will work on large-scale data projects, leveraging
Azure services
and
Databricks
to deliver predictive insights and optimize business outcomes.
Key Responsibilities:
- Develop and deploy machine learning models using Azure Machine Learning and Databricks.
- Build data pipelines and perform ETL using Azure Data Factory and Databricks.
- Conduct data preprocessing, feature engineering, and model tuning for large datasets.
- Implement end-to-end ML workflows including training, validation, and deployment.
- Collaborate with data engineers, analysts, and business teams to define requirements and deliver actionable insights.
- Apply MLOps best practices for model versioning, monitoring, and CI/CD in Azure.
- Create dashboards and visualizations using Power BI or similar tools.
Required Skills & Qualifications:
- Strong proficiency in Python for Data Science and Machine Learning.
- Hands-on experience with Azure Databricks, Azure Machine Learning, and Azure Data Lake.
- Solid understanding of machine learning algorithms, deep learning, and statistical modeling.
- Experience with Spark for distributed data processing.
- Familiarity with MLOps, CI/CD pipelines, and Azure DevOps.
- Excellent problem-solving and communication skills.
Preferred Qualifications:
- Microsoft certifications such as Azure Data Scientist Associate or Azure Solutions Architect.
- Experience with Power BI for visualization.
- Knowledge of big data technologies and cloud security best practices.
Education:
- Bachelor's or Master's Degree in Data Science, Computer Science, Statistics, or related field.
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