Data Scientist

Roles- Data Scientist

Locations- NYC, NY (Locals only)

Durations- 6+ Months

Rate- $55/hr on c2c

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USC/GC/H4/H1

About the Team

Fitch Ratings is seeking a highly motivated Data Scientist to join its Risk Research & Analytics team. In this role, you will support data-driven risk research initiatives that influence strategic decision-making for some of the world’s leading financial institutions and organizations.

As part of this team, you will work with proprietary risk datasets to analyze, interpret, and generate insights across multiple use cases. Your contributions will directly support product development, research publications, and advanced analytics initiatives. This role offers exposure beyond traditional data science boundaries, with close collaboration across risk management, economics, political risk, and technology domains.

Role Overview

As a Data Scientist, you will be responsible for designing, developing, and deploying quantitative and machine learning models that drive advanced analytics, insights, and AI-enabled products. You will collaborate closely with Country Analysts, Industry Analysts, Economists, Political Scientists, fellow Data Scientists, and Backend Engineers to deliver scalable, interpretable, and production-ready solutions.

You will play a key role in enhancing Fitch’s modeling frameworks, particularly in the areas of risk analytics, NLP-driven insights, and generative AI use cases, while adapting solutions to meet evolving customer and market needs.

Key Responsibilities / How You’ll Make an Impact

• Prototype, test, and implement innovative approaches to extract insights from both structured and unstructured datasets for Fitch’s core clients, including Corporates, Banks, Professional Services firms, and Asset Managers.
• Design, build, and maintain robust machine learning and data pipelines to support experimentation, validation, and production deployment.
• Develop, optimize, and monitor quantitative risk models supporting analytics platforms and generative AI applications, leveraging Fitch’s proprietary NLP data generation processes.
• Collaborate cross-functionally with Economists, Industry Analysts, Political Scientists, Product teams, and Developers to translate domain knowledge into effective analytical solutions.
• Communicate model assumptions, outputs, and methodologies clearly to non-technical stakeholders, ensuring transparency and interpretability of insights.
• Contribute to continuous improvement of modeling frameworks, data quality, and analytical methodologies in a fast-paced, collaborative environment.

Required Qualifications / You May Be a Good Fit If You Have

• Strong hands-on experience querying, cleaning, compiling, and analyzing large and complex datasets.
• Practical exposure to computational social science techniques, including:
  • Data mining and data visualization
  • Natural Language Processing (NLP) and text analytics
  • Basic time-series forecasting and machine learning models
• Experience developing, refining, validating, and monitoring NLP models in production or research environments.
• Proficiency in Python and R, along with relevant libraries such as:
  • Python: NumPy, Pandas, Scikit-learn, PyTorch
  • R: Tidyverse, Caret, ggplot2
• Understanding of model evaluation metrics, validation techniques, and performance monitoring.
• Ability to translate non-technical business or research ideas into well-defined analytical approaches, features, and model outputs.
• Familiarity with experiment tracking and model management tools such as DVC, Weights & Biases, or similar platforms.
• Demonstrated experience working with interpretable AI and explainability techniques.

Preferred (Nice to Have):

• Exposure to scenario analysis, stress testing, simulation modeling, rare event modeling, or stochastic modeling.
• Familiarity with data storage, ingestion, and access tools such as SQL, APIs, Selenium, AWS S3, or SageMaker.

What Would Make You Stand Out

• Experience working with cloud-based data and analytics platforms such as AWS, Databricks, or Snowflake.
• Advanced degree or relevant certifications in Data Science, Machine Learning, NLP, Statistics, or related fields.
• Familiarity with DevOps concepts, CI/CD pipelines, and production ML workflows.
• Hands-on experience with model experimentation, tracking, and lifecycle management tools like MLflow or Weights & Biases.
• Proven examples where technical solutions directly influenced business decisions or customer outcomes.
• Experience working in agile, fast-paced environments with cross-functional teams.
• Customer-facing exposure, including gathering requirements, understanding end-user needs, and building strong collaborative relationships.

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