At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are-with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. 

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. 

Data Solutions
Data Solutions division is the commercial data business of Moody’s Analytics, bringing together a vast catalogue of data to help business decision-makers assess risks and opportunities. We are best known for Orbis, the world’s most comprehensive database of public and private companies. We are also the definitive source of ratings-related data for companies and securities that have been rated by Moody’s Investors Service. We strive to deliver convenience and insight to our customers by eliminating the hassle of sourcing, preparing, and accessing data, adding value when decisions need to be made. Any analytical activity depends on reliable and accessible data, and we are proud to be a mission-critical information resource for decision-makers around the world.

Key Responsibilities:
- Design, develop, and deploy AI and ML applications using Python, Web Scraping, Flask, Selenium, PyTorch, TensorFlow, or similar frameworks.
- Build and enhance AI-integrated applications that meet business needs.
- Analyse complex datasets to derive actionable insights and guide decision-making.
- Collaborate with cross-functional teams to translate business requirements into effective analytical solutions.
- Implement and optimize advanced AI algorithms and logics for scalability in production environments.
- Utilize AWS and GCP services to deploy and manage AI applications effectively.
- Communicate findings through compelling visualizations and detailed reports

Requirement Qualifications:
- B. Tech/BE degree in Computer Science, Data Science, or related fields; a master’s degree is a plus.
- 1-2 years of proven experience as a Data Scientist (or in a similar role) with a strong focus on Python and AI/ML technologies.
- Strong understanding of statistical analysis, machine learning and web scraping techniques.
- Expertise in data manipulation libraries (e.g., Pandas, NumPy) and data visualization tools.
- Proficiency in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).
- Deep understanding of machine learning and deep learning techniques.
- Familiarity with general AI concepts and frameworks.
- Experience with AWS and GCP cloud platforms, including key technologies such as EC2, S3, RDS, IAM and Lambdas
- Strong collaborative skills, ability to manage multiple projects simultaneously meet deadlines.
- Excellent problem-solving abilities and communication skills as well as attention to detail.
- Eagerness to learn new technologies and adapt to industry trends and changes.

Additional Preferred Qualifications:
- Working knowledge of AWS DevOps and CI/CD practices.
- Knowledge of front-end technologies, such as ReactJS, HTML, and CSS.
- Experience in full-stack development, including integrating AI models with user interfaces.
- Working knowledge of LLMs and familiarity with Generative AI models like OpenAI GPT, Google Gemini, and Claude

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.