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Data Science Lead
1 month ago
We are seeking a seasoned Data Scientist to spearhead the design, development, and deployment of cutting-edge Azure Machine Learning models that drive business growth. As a key member of our team, you will apply advanced machine learning techniques, collaborate closely with engineering and DevOps teams to ensure seamless deployment and monitoring of models in production, and implement CICD practices for continuous improvement and reliability.
- Develop and implement high-performance machine learning models for various business use cases, ensuring alignment with strategic objectives and delivering actionable insights.
- Preprocess, clean, and explore large datasets, leveraging feature engineering and data transformation techniques to enhance model quality and accuracy.
- Deploy models into production environments using Azure Machine Learning and monitor performance, implementing adjustments to maintain optimal results.
- Implement CICD pipelines for model deployment and updates, ensuring reliable and reproducible workflows in collaboration with DevOps teams.
- Conduct A/B testing, evaluate model accuracy, and iterate based on feedback to improve performance over time.
- Troubleshoot and resolve model performance, data quality, and system integration issues within the production environment.
- Masters degree in Data Science, Computer Science, Statistics, or related field.
- At least 11 years of experience in Data Science and Analytics, with a focus on hands-on roles.
- Proficiency in Python, R, SQL, and machine learning libraries (e.g., scikit-learn).
- Hands-on experience with Azure ML, Azure Data Factory, and cloud deployment of machine learning models.
- Familiarity with CICD tools and practices, such as Jenkins, Git, and containerization (Docker), to automate and streamline the model deployment process.
- Strong analytical and statistical skills with knowledge of data preprocessing, model selection, and evaluation techniques.
- Excellent communication skills to effectively convey insights and recommendations to both technical and non-technical stakeholders.
$140,000 - $200,000 per year, depending on location and experience.
