Senior Data Scientist
1 week ago
Within the Digital Finance team, the Senior Data Scientist will be responsible for developing machine learning solutions for high-profile data science initiatives. The Senior Data Scientist will notably focus on designing and training predictive analytics models, crafting signals from unstructured data and creating high-value-added solutions converting quantitative predictions into actionable insights for the business.
A successful candidate will demonstrate an excellent knowledge of the various steps of a machine learning project, including modeling, data engineering, and MLOps. The candidate should also be innovation-minded, result-oriented, autonomous, and able to deliver finished products, sometimes under short deadlines.
The data science team will work closely with technology teams, rating and research teams, and other departments. The candidate should therefore be able to collaborate across multiple divisions and communicate clearly and understandably to business representatives unfamiliar with data science. The Senior Data Scientist will be a mentor of junior team members and participate actively to their growth.
The Senior Data Scientist will also strive to meet Moody’s values: openness, diversity, inclusivity, respect, and a willingness to learn.
The duties of the Senior Data Scientist include:
- Select and train machine learning models for predictive analytics, sometimes with relatively small and unbalanced datasets.
- Build solutions predicting activities and extracting signals from multiple data sources.
- Design explainability tools understandable by non-data scientists.
- Collaborate with tech teams to create data ingestion pipelines connected to sources spread across different parts of the organization and delivered in varying formats.
- Support tech teams in developing MLOps solutions and putting models in production.
- Evaluate and select the best tools and IT architectures with tech teams.
- Support tech teams in the management of cloud resources.
- Communicate results to business stakeholders and decision-makers.
- Collaborate with subject matter experts from ratings and research teams to incorporate fundamental expertise into machine learning models.
- Mentor team members without data science backgrounds, as required, and foster a culture of knowledge sharing and learning.
- Stay current with the latest research and technology developments.
- Speak at internal and external events, as required
Qualifications
- Master’s degree or Ph.D. in data science, computer science, statistics, mathematics, or a related quantitative field.
- 3+ years in machine learning, with a strong knowledge of algorithms and principles.
- Proven track record of successfully modeling, building, and putting in production machine learning applications.
- Deep understanding of the tools explaining machine learning predictions.
- Expertise in Python and SQL.
- Previous experience with Spark is a plus.
- Strong knowledge of Git and collaboration principles, ability to review pull requests.
- Proven experience in natural language processing.
- Excellent communication and presentation skills, with the ability to explain complex analytical concepts to people from other fields.
- Previous experience in corporate finance or debt markets is preferred.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion, national origin, citizen status, marital status, physical or mental disability, military or veteran status, sexual orientation, gender identity, gender expression, genetic information, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email accommodations@moodys.com. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications.
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