Senior Data Scientist

About the Role

We are seeking a Senior Data Scientist with over 6 years of experience to lead and implement

advanced AI/ML solutions across cloud and on-premise infrastructures. The ideal candidate has

strong technical expertise in machine learning, cloud services, and software engineering

practices, complemented by a robust understanding of automation, data workflows, and modern

DevOps techniques.

Key Responsibilities

1. Model Development & Optimization:

• 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.

2. Cloud-Based Generative AI 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.

3. Programming and Scripting:

• Write efficient code using Python, SQL, and Bash scripting for data analysis, model training, and deployment.
• Automate repetitive processes to improve operational efficiency.

4. Infrastructure & CI/CD:

• 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.

5. Testing and Monitoring:

• 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.

6. Data Management & APIs:

• 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.

7. Collaboration and Documentation:

• 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.

Required Skills and Qualifications

• Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or a related field.
• Technical Expertise:

Proficiency in Python, SQL, and Bash scripting for automation and analysis.

Experience with cloud-based AI services like AWS SageMaker, Azure ML, and others.

Hands-on knowledge of IaC tools (e.g., Terraform, CloudFormation).

Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or CircleCI.

Strong understanding of databases, including NoSQL technologies (e.g., MongoDB, Cassandra).

• Testing and Monitoring: Expertise in automated testing frameworks like Selenium and Pytest. Experience implementing model drift monitoring to ensure consistent performance.
• Soft Skills: Excellent problem-solving and analytical skills. Strong communication and collaboration abilities for working across diverse teams.