Data Scientist bangalore

22 hours ago

Karnataka, India Globant Full time

**We are a digitally native company that helps organizations reinvent themselves and unleash their potential. We are the place where innovation, design and engineering meet scale. With more than 29,000+ employees and present in 33 countries across 5 continents, we’re partnering with companies like Google, Electronic Arts, and Santander, among others.**

**Location**:Pune OR Bangalore (Working from client location)
- Hybrid Model

**Experience**:8+ Years

Data Scientist

About the Role, We are seeking a Data Scientist with over 8 years of experience to lead and implement advanced AI/ML solutions across cloud and on-premise infrastructures.

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.

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.

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 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.

Certifications in cloud platforms (AWS, Azure, or GCP).
- Experience deploying large-scale generative AI models.
- Understanding of microservices architecture and containerization (e.g., Docker, Kubernetes).

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