need 12+ experience
Joining as a Data Scientist to support risk research and analysis, you will help shape the strategic decisions of the worlds leading organizations. Candidates will have the opportunity to explore, analyze, and write about our proprietary risk data for different use cases and aid in product development. As a member of our team, your role will go beyond conventional boundaries. You will collaborate with experts across risk management and other domains.
As a Data Scientist, you will design, build, and deploy quantitative models that power advanced analytics and insights for our clients. You will work closely with country analysts, industry analysts, economists, political scientists, data scientists, and backend developers to deliver interpretable, scalable solutions. Your expertise will help us innovate and adapt our modeling frameworks to address diverse customer needs in a fast-paced, collaborative environment.
How Youll Make an Impact:
• Prototype and test new approaches for extracting insights from structured and unstructured data for our core customer base Corporates, Banks, Professional Services, and Asset Managers
• Develop and maintain robust ML and data pipelines for experimentation and deployment.
• Design, build, and optimize risk models for analytics and generative AI applications using our proprietary NLP data generation process.
• Collaborate cross functionally with Economists, Industry Analysts, Political Scientists, and Developers.
• Explain ML/NLP model outputs and methodologies to non-technical stakeholders.
You May be a Good Fit if:
• Substantial experience querying, cleaning, compiling, and analyzing big data.
• Familiarity applying various computational social science methods including data mining, data visualization, natural language processing, text analysis, and basic time series forecasting and machine learning models.
• Familiarity with scenario analysis/stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required.
• Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.).
• Proven experience developing, refining, and monitoring NLP models.
• Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required.
• Understanding model evaluation methods and metrics.
• Ability to operationalize non-technical ideas into relevant research designs, features, and model outputs.
• Familiarity with experiment tracking and model management tools (e.g., DVC, Weights & Biases).
• Demonstrated experience with interpretable AI techniques.
What Would Make You Stand Out:
• Exposure to different cloud-based data and analytics platforms (e.g. AWS, DataBricks, Snowflake).
• Advanced degree or certification in NLP, ML, or related fields.
• Familiarity with DevOps practices and tools.
• Hands-on experience with experimentation and model tracking tools (e.g., MLFlow, Weights & Biases).
• Demonstrable impact of technical solutions or projects on decision-making
• Experience working in fast-paced, agile environments.
• Customer-facing experience, notably in understanding end user needs and building collaborative relationships.
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