Job Description: Pay Range: $55hr - $60hr Responsibilities: Data Analysis and Modeling:
- nalyze large datasets to identify trends, patterns, and insights.
- Develop and implement machine learning models using Python and Azure Client.
- Perform data preprocessing, feature engineering, and model evaluation.
zure Data Bricks:
- Utilize Azure Data bricks for data processing, transformation, and analysis.
- Develop and maintain ETL pipelines using Apache Spark on Data bricks.
- Collaborate with data engineers to ensure data quality and integrity.
Machine Learning Operations:
- Deploy and monitor machine learning models in production environments.
- Use MLflow for tracking experiments, managing model lifecycle, and versioning.
- Implement best practices for model deployment, scalability, and performance.
Collaboration and Communication:
- Work closely with cross-functional teams, including data engineers, software developers, and business analysts.
- Communicate findings and insights to stakeholders through reports, dashboards, and presentations.
Requirements:
- Deep skills in creating models to develop scalable solutions.
- Experience in deploying models and putting models into production.
- Good understanding of end-to-end data science projects - data intuition validation, model design, implementation, validation and testing, and deployment.
- Proven track record of building and demonstrating business value from predictive models and data products.
- bility to write clean, understandable, well-documented code, following best practices.
- Experience with Machine Leaning algorithms - supervised & unsupervised.
- Experience dealing with both structured & unstructured datasets and drawing the insights from the data.