MLOps(NCS/Job/ 1407)

Job Description:

We are seeking a highly skilled Data Scientist who specializes in MLOps to join our team. The successful candidate will be responsible for the development, deployment, and automation of machine learning models. This role requires a deep understanding of machine learning operations (MLOps) to ensure efficient and scalable model management. Additionally, expertise in time series forecasting and Flask for web applications is desired.

Key Responsibilities:

1. Model Development and Deployment:

   • Design, develop, and deploy machine learning models tailored to large datasets.
   • Ensure models are scalable and production-ready, capable of handling real-world data and scenarios.

2. Automation:

   • Implement automation processes for model training, testing, and deployment.
   • Develop and maintain CI/CD pipelines for continuous integration and delivery of machine learning models.

3. End-to-End Workflows:

   • Create and manage end-to-end workflows for machine learning projects, from data collection and preprocessing to model deployment and monitoring.
   • Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.

4. Time Series Forecasting:

   • Develop and implement time series forecasting models to predict future trends and patterns.
   • Utilize statistical and machine learning techniques to improve forecasting accuracy.

5. Web Applications with Flask:

   • Develop web applications using Flask to provide user-friendly interfaces for machine learning models.
   • Integrate machine learning models into web applications to enable real-time predictions and insights.

6. Monitoring and Visualization:

   • Use tools like Splunk to monitor model performance and visualize data insights.
   • Implement monitoring solutions to track model accuracy, performance, and drift over time.

Qualifications:

• Proven experience in developing machine learning solutions for large datasets.
• Strong expertise in MLOps, including model development, deployment, and automation.
• Proficiency in programming languages such as Python.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Expertise in time series forecasting techniques and tools.
• Experience with Flask for developing web applications.
• Familiarity with monitoring and visualization tools like Splunk.
• Excellent problem-solving skills and the ability to work in a collaborative environment.

Primary Skills:

• Core: Data Scientist with MLOps Expertise
• Data Science and Analytics - One to Three Years
• Project Manager - One to Three Years
• MLOps - One to Three Years
• PSP Defined SCU: Data Engineering_Senior Data Ops Professional