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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate Director, Data Scientist - **Company:** Fitch Solutions - **Location:** UK - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Business Analytics Applications, Data Analysis, BASIC (Programming Language), Big Data, Cloud Database, Data Mining, Data Visualization, DevOps, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Selenium, SQL Databases, Unstructured Data, Pytorch, Large Language Models, Snowflake, Model Validation, Backend, Pandas, Scikit Learn, Machine Learning Operations, Text Analysis, Data Pipelines, Database Tools and Utilities, Databricks, Data Generation - **Published:** July 24, 2026 - **Apply:** https://www.totaljobs.com/job/director-of-data/fitch-solutions-job107741704 ## About the Role * 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. ## Description 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 You'll 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Vectorize all the things! 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