- Company Name
- Fitch Solutions
- Job Title
- Data Scientist
- Job Description
-
**Job title**
Data Scientist
**Role Summary**
Design, build, and deploy quantitative risk models and machine‑learning pipelines to power advanced analytics and generative AI applications for global market risk research. Collaborate with economists, industry analysts, political scientists, and developers to translate complex datasets into interpretable insights for clients across financial services and asset management.
**Expectations**
- Proven ability to query, clean, and analyze large, heterogeneous datasets.
- Hands‑on experience with Python or R and their scientific libraries (numpy, pandas, scikit‑learn, PyTorch, tidyverse, caret, ggplot, etc.).
- Solid background in NLP, text analysis, and basic time‑series/forecasting techniques.
- Familiarity with scenario/stress‑testing, rare‑event, or stochastic modeling is a plus.
- Demonstrated competence in model evaluation, interpretability, and operationalizing ML solutions.
**Key Responsibilities**
- Prototype and test novel approaches for extracting insights from structured and unstructured data.
- Develop, maintain, and extend robust ML and data pipelines for experimentation and production deployments.
- Design, build, and optimize risk models for analytics and generative‑AI use cases using proprietary NLP data.
- Collaborate across functions (economists, analysts, developers) to refine model features and outputs.
- Communicate model methodologies and results to non‑technical stakeholders.
- Track experiments and manage models using tools such as DVC, Weights & Biases, MLFlow, or equivalent.
- Monitor model performance, enforce governance, and iterate on models to meet evolving business needs.
**Required Skills**
- Big‑data manipulation (SQL, data warehousing; optional familiarity with Selenium, S3, SageMaker, APIs).
- Programming: Python or R with key libraries; proficiency in natural‑language processing and machine‑learning frameworks.
- Experience building NLP models (training, fine‑tuning, deployment).
- Knowledge of experiment tracking and model management systems.
- Interpretability techniques for AI models.
- Excellent communication and collaborative skills.
- Ability to translate business problems into research designs, feature engineering, and model outputs.
**Required education & certifications**
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or related field.
- Advanced degree (M.Sc./Ph.D.) or professional certification in Machine Learning, NLP, or a related domain is highly desirable.
- Familiarity with cloud‑based data platforms (AWS, Databricks, Snowflake) and DevOps practices is a plus.