—
BMI is currently seeking a Data Scientist Lead based out of our London or Manchester office. BMI's systematic, independent and data-driven market insights, analysis and forecasts enable customers to recognize and assess risks and opportunities across markets and industries. At BMI, we’re proud of the work we do to help our clients manage risks and opportunities in global markets, which began in 1984 and continues to this day. By stepping into a role here, you will help shape the strategic decisions of the world’s leading organizations. Our people are at the heart of everything we do, and we continuously strive to offer our colleagues a great place to work, with opportunities to learn, innovate, develop their careers, and serve the community. BMI's team integrates cross-domain expertise (Economics, Politics, 20+ industries, ESG, Commodities) and computer science to create systematic country-by-country risk analytics and time series forecasts that are transparent and can be validated. We build and maintain robust models that our customers use to identify and manage country risks. Joining as a Data Scientist Lead to support risk research and analysis, you will lead the ideation and prioritization of BMI’s Data Science roadmap alongside BMI’s Product Team, and provide leadership and coordination to BMI’s growing team of Data Scientists. As BMI’s Data Science Lead, you will participate and oversee the design, build, and deployment of quantitative models that power advanced analytics and insights for our clients. You will work closely with Developers, Product and Content teams (country analysts, industry analysts, economists, political scientists) 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 . 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. 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. 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., 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. Demonstrated experience with interpretable AI techniques. Leadership / management experience of a Data Science function Strong record of collaboration across Data Science, Technology and Product teams 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. 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. Hybrid Work Environment: 3 days a week in office required Dedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity Retirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals 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 Dedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law. • LI-hybrid
| Skill | Source | Confidence |
|---|---|---|
| R | llm_hard |
100%
|
| NLP | llm_hard |
100%
|
| Large Language Models (LLMs) | llm_hard |
100%
|
| Python | llm_hard |
100%
|
| Data Pipelines | llm_hard |
80%
|
| Model Deployment | llm_hard |
80%
|
| AWS (SageMaker, EC2, S3) | llm_hard |
80%
|
| Time Series Analysis | llm_hard |
80%
|
| Forecasting | llm_hard |
80%
|
| Model Performance Optimization | llm_hard |
80%
|
| SQL | llm_hard |
80%
|
| Data Wrangling | llm_hard |
80%
|
| Data Cleaning | llm_hard |
80%
|
| Skill | Source | Confidence |
|---|---|---|
| Analytical Thinking | llm_soft |
100%
|
| Innovation | llm_soft |
100%
|
| Documentation | llm_soft |
100%
|
| Leadership | llm_soft |
100%
|
| Team Leadership | llm_soft |
100%
|
| Strategic Thinking | llm_soft |
100%
|
| Mentoring | llm_soft |
100%
|
| Collaboration | llm_soft |
100%
|
| Cross-Team Collaboration | llm_soft |
100%
|
| Problem-Solving | llm_soft |
100%
|
| Critical Thinking | llm_soft |
100%
|
| Building Client Relationships | llm_soft |
80%
|
| Technical Writing | llm_soft |
80%
|
| Customer Service | llm_soft |
80%
|
| Cross-Functional Communication | llm_soft |
80%
|
| Query | Country | Status | Response ms | Created |
|---|---|---|---|---|
| Data Science and AI Lead | extracted | 10325 | 2026-03-22 03:16 | |
| Data Science and AI Lead | classified | 440 | 2026-03-21 21:16 | |
| graduate data scientist in Manchester | gb | processed | 10738 | 2026-03-21 17:20 |
{
"job_id": "3OYEtRVqeU2iMFhhAAAAAA==",
"job_city": "Manchester",
"job_state": null,
"job_title": "Data Science and AI Lead",
"job_salary": null,
"job_country": "GB",
"job_benefits": null,
"job_latitude": 53.480759299999995,
"job_location": "Manchester",
"job_onet_soc": "15111100",
"apply_options": [
{
"is_direct": false,
"publisher": "Jooble",
"apply_link": "https://uk.jooble.org/rjdp/-8691106721791887357?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
},
{
"is_direct": false,
"publisher": "Talents By StudySmarter",
"apply_link": "https://talents.studysmarter.co.uk/companies/latinx-in-ai-lxai/manchester/data-science-and-ai-industrial-placement-manchester-19815087/?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
},
{
"is_direct": null,
"publisher": "Jooble",
"apply_link": "https://uk.jooble.org/rjdp/-8691106721791887357"
}
],
"employer_logo": null,
"employer_name": "Fitch Group",
"job_is_remote": false,
"job_longitude": -2.2426304999999997,
"job_posted_at": "18 days ago",
"job_publisher": "Jooble",
"job_apply_link": "https://uk.jooble.org/rjdp/-8691106721791887357?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic",
"job_highlights": {},
"job_max_salary": null,
"job_min_salary": null,
"job_description": "BMI is currently seeking a Data Scientist Lead based out of our London or Manchester office.\n\nBMI's systematic, independent and data-driven market insights, analysis and forecasts enable customers to recognize and assess risks and opportunities across markets and industries. At BMI, we’re proud of the work we do to help our clients manage risks and opportunities in global markets, which began in 1984 and continues to this day. By stepping into a role here, you will help shape the strategic decisions of the world’s leading organizations. Our people are at the heart of everything we do, and we continuously strive to offer our colleagues a great place to work, with opportunities to learn, innovate, develop their careers, and serve the community.\n\nBMI's team integrates cross-domain expertise (Economics, Politics, 20+ industries, ESG, Commodities) and computer science to create systematic country-by-country risk analytics and time series forecasts that are transparent and can be validated. We build and maintain robust models that our customers use to identify and manage country risks.\n\nJoining as a Data Scientist Lead to support risk research and analysis, you will lead the ideation and prioritization of BMI’s Data Science roadmap alongside BMI’s Product Team, and provide leadership and coordination to BMI’s growing team of Data Scientists.\n\nAs BMI’s Data Science Lead, you will participate and oversee the design, build, and deployment of quantitative models that power advanced analytics and insights for our clients. You will work closely with Developers, Product and Content teams (country analysts, industry analysts, economists, political scientists) 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 .\n\nOwn the technical roadmap, setting standards for data quality, feature engineering, model governance to ensure scalable, reliable delivery.\nMentor 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\nEstablish responsible AI practices, including bias testing, explainability, performance monitoring, and documentation; collaborate with legal/compliance on data usage and model transparency.\nPrototype and test new approaches for extracting insights from structured and unstructured data for our core customer base\nDevelop and maintain robust ML and data pipelines for experimentation and deployment.\nDesign, build, and optimize risk models for analytics and generative AI applications using our proprietary NLP data generation process.\nExperience setting standards, code review, elevating best practices, hiring and developing talent, and fostering a culture of rigor, collaboration, and delivery.\nProven experience translating business problems into measurable AI solutions, defining success metrics, prioritizing roadmaps, and driving adoption and impact.\nSubstantial experience querying, cleaning, compiling, and analyzing big data.\nFamiliarity 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.\nFamiliarity with scenario analysis/stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required.\nSubstantial experience with Python, R, and relevant libraries (e.g., Proven experience developing, refining, and monitoring NLP models.\nFamiliarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required.\nDemonstrated experience with interpretable AI techniques.\n\nLeadership / management experience of a Data Science function\nStrong record of collaboration across Data Science, Technology and Product teams\nExposure to different cloud-based data and analytics platforms (e.g. AWS, DataBricks, Snowflake).\nAdvanced degree or certification in NLP, ML, or related fields.\nFamiliarity with DevOps practices and tools.\nDemonstrable impact of technical solutions or projects on decision-making\nExperience working in fast-paced, agile environments.\nCustomer-facing experience, notably in understanding end user needs and building collaborative relationships.\n\nHybrid Work Environment: 3 days a week in office required\nDedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity\nRetirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals\nComprehensive healthcare offerings that enable physical, mental, financial, social, and occupational wellbeing\nSupportive Parenting Policies: Family-friendly policies, including a generous global parental leave plan, designed to help you balance career and family life effectively\nDedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community\n\nIf you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.\n\nWe evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.\n• LI-hybrid",
"job_google_link": "https://www.google.com/search?q=jobs&gl=gb&hl=en&udm=8#vhid=vt%3D20/docid%3D3OYEtRVqeU2iMFhhAAAAAA%3D%3D&vssid=jobs-detail-viewer",
"employer_website": "https://www.fitch.group",
"job_onet_job_zone": "5",
"job_salary_period": null,
"job_apply_is_direct": false,
"job_employment_type": null,
"job_employment_types": [],
"job_posted_at_timestamp": 1772496000,
"job_posted_at_datetime_utc": "2026-03-03T00:00:00.000Z"
}