Data Scientist

Company:IT Services Organization

Key Skills: Python, SQL, Bash, AWS SageMaker, Azure ML, Bedrock, Code Whisperer, Terraform, CloudFormation, Jenkins, GitHub Actions, CircleCI, MongoDB, Cassandra, Selenium, Pytest, RESTful APIs, CI/CD, Model Drift Monitoring, Automation, Data Pipelines, Docker, Kubernetes, Generative AI, Cloud Certifications.

Roles and Responsibilities:

• Design and implement machine learning models with a focus on performance, scalability, and adaptability to address real-world challenges.
• Monitor and mitigate model drift to maintain the accuracy and relevance of deployed solutions.
• Develop and deploy AI/ML applications using services like SageMaker, Bedrock, Code Whisperer, and Azure ARM.
• Optimize workflows for generative AI use cases on cloud platforms, ensuring seamless integration with existing systems.
• Write efficient code using Python, SQL, and Bash scripting for data analysis, model training, and deployment.
• Automate repetitive processes to improve operational efficiency.
• Build and manage robust Infrastructure as Code (IaC) solutions to automate cloud resource provisioning.
• Integrate and utilize CI/CD tools to streamline code delivery and deployment pipelines.
• Implement automated testing frameworks such as Selenium and pytest for quality assurance.
• Develop systems for continuous monitoring of APIs, data pipelines, and models in production.
• Design and optimize databases, including NoSQL systems, for efficient data storage and retrieval.
• Build, maintain, and enhance RESTful APIs to enable seamless integration with external applications.
• Collaborate with cross-functional teams to understand business needs and translate them into technical solutions.
• Document workflows, architectures, and model outputs to ensure clarity and maintainability.

Experience Requirement:

• 8-12 years of experience in designing, developing, and optimizing advanced AI/ML solutions across cloud and on-premise infrastructures.
• Strong technical expertise in Python, SQL, Bash scripting, and automation tools.
• Hands-on experience in developing cloud-based AI solutions using AWS SageMaker, Bedrock, Azure ML, Code Whisperer.
• Experience with IaC tools like Terraform or CloudFormation and CI/CD tools such as Jenkins, GitHub Actions, or CircleCI.
• Proven experience in building scalable data workflows, testing frameworks (Selenium, pytest), and production monitoring systems.
• Practical exposure to NoSQL databases such as MongoDB and Cassandra.
• Involved in deploying and maintaining large-scale generative AI models and automation of cloud infrastructure.
• Experience in collaborating with cross-functional teams and documenting technical solutions.

Education: B.Tech.