Hybrid Data Science Lead

at Fitch Group, Inc.

• Job title: Data Science Lead
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Numpy, Pandas, Python, PyTorch, Selenium, SQL
• Location requirements: Hybrid, London, United Kingdom

About the role

• Data Scientist Lead overseeing BMI's Data Science roadmap alongside the Product Team. Collaborating cross-functionally to deliver scalable solutions for risk analytics and insights.

Responsibilities

• Own the technical roadmap, setting standards for data quality, feature engineering, model governance to ensure scalable, reliable delivery.
• Mentor and upskill the data science team, guiding best practices in experimentation, causal inference, NLP/LLM, and time-series forecasting, review code and models for rigor and reproducibility
• Establish responsible AI practices, including bias testing, explainability, performance monitoring, and documentation; collaborate with legal/compliance on data usage and model transparency.
• Prototype and test new approaches for extracting insights from structured and unstructured data for our core customer base
• 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 model outputs and methodologies to non-technical stakeholders.

Requirements

• Experience setting standards, code review, elevating best practices, hiring and developing talent, and fostering a culture of rigor, collaboration, and delivery.
• Proven experience translating business problems into measurable AI solutions, defining success metrics, prioritizing roadmaps, and driving adoption and impact.
• Technical communication skills explaining complex models, uncertainty, and trade-offs to non-technical audiences; creating clear documentation.
• 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.

Benefits

• Hybrid Work Environment: 3 days a week in office required
• A Culture of Learning & Mobility: Dedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity
• Investing in Your Future: Retirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals
• Promoting Health & Wellbeing: Comprehensive healthcare offerings that enable physical, mental, financial, social, and occupational wellbeing
• Supportive Parenting Policies: Family-friendly policies, including a generous global parental leave plan, designed to help you balance career and family life effectively
• Inclusive Work Environment: A collaborative workplace where all voices are valued, with Employee Resource Groups that unite and empower our colleagues around the globe
• Dedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community