At a Glance
- Tasks: Join BMI as a Data Scientist and shape strategic decisions with data-driven insights.
- Company: BMI is a leading firm providing independent market analysis for nearly 40 years.
- Benefits: Enjoy hybrid work, comprehensive healthcare, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on learning and community engagement.
- Why this job: Make a real impact by collaborating with experts across various industries.
- Qualifications: Experience in big data analysis and familiarity with Python and ML models required.
The predicted salary is between 60000 - 80000 £ per year.
BMI is currently seeking a Data Scientist based out of London or Manchester. 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. For almost 40 years, we have provided impartial views to support our customers’ strategic plans and investment decisions.
As a member of our team, your role will go beyond conventional boundaries. You will collaborate with industry experts, thought leaders, and visionary executives, collectively working towards shaping the future of businesses that span a multitude of sectors. 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.
About The Team
BMI's team integrates cross-domain expertise (Economics, Politics, 20+ industries, ESG, Commodities) and computer science to create systematic country risk analytics 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 to support risk research and analysis, you will help shape the strategic decisions of the world’s leading organizations.
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.
You May Be a Good Fit If
- Substantial experience querying, cleaning, compiling, and analyzing big data.
- Strong appreciation of software engineering fundamentals such as code quality, code reviews, unit testing and developing code that is supportable and maintainable.
- Experience of developing quantitative models under source control that are fully documented and reproducible.
- 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.
- 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.
- Understanding model evaluation methods and metrics.
- Ability to operationalize non-technical ideas into relevant research designs, features, and model outputs.
- Demonstrated experience with interpretable AI techniques.
What Would Make You Stand Out
- Degree in a quantitative subject (e.g. mathematics, physics, engineering or data science).
- Experience of working as a developer in a corporate environment and production support experience.
- Exposure to different cloud-based data and analytics platforms (e.g. AWS, DataBricks, Snowflake).
- Advanced degree or certification in NLP, ML, or related fields.
- Hands‑on experience with experimentation and model tracking tools (e.g., MLFlow, Weights & Biases).
- Customer‑facing experience, notably in understanding end user needs and building collaborative relationships.
Why Choose Fitch
- 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.
Fitch is committed to providing global securities markets with objective, timely, independent, and forward‑looking credit opinions. To protect Fitch’s credibility and reputation, our employees must take every precaution to avoid conflicts of interest or any appearance of a conflict of interest.
Associate Director, Data Scientist employer: Fitch Solutions
Contact Detail:
Fitch Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate Director, Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with BMI employees on LinkedIn. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Prepare for interviews by diving deep into BMI's work and values. Understand their approach to data-driven insights and think about how your skills can contribute to their mission. Show them you’re not just another candidate!
✨Tip Number 3
Practice your storytelling skills! Be ready to share specific examples of your past projects and how they relate to the role. This will help you stand out and demonstrate your experience effectively.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of the BMI team.
We think you need these skills to ace Associate Director, Data Scientist
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Scientist role. Highlight your experience with data analysis, machine learning, and any relevant projects that showcase your skills. We want to see how you can contribute to our mission at BMI!
Showcase Your Technical Skills: Don’t hold back on your technical expertise! Mention your proficiency in Python, R, and any libraries you've used. If you've worked with NLP or ML models, let us know how you’ve applied them in real-world scenarios. This is your chance to shine!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to explain your experiences and achievements. We appreciate a well-structured application that makes it easy for us to see your potential.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Fitch Solutions
✨Know Your Data Inside Out
As a Data Scientist, you'll be expected to have a solid grasp of data querying and analysis. Brush up on your skills with Python, R, and relevant libraries like pandas and scikit-learn. Be ready to discuss specific projects where you've cleaned, compiled, and analysed big data, showcasing your ability to derive insights.
✨Showcase Your Collaboration Skills
At BMI, teamwork is key. Prepare examples of how you've worked cross-functionally with different experts, such as economists or developers. Highlight your experience in explaining complex ML/NLP concepts to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between technical and non-technical teams.
✨Demonstrate Your Problem-Solving Approach
Be prepared to discuss how you've tackled challenges in model development and deployment. Share specific instances where you've optimised risk models or developed robust ML pipelines. This will show your analytical thinking and your ability to innovate in a fast-paced environment.
✨Prepare for Technical Questions
Expect questions about model evaluation methods and metrics, as well as your familiarity with tools like SQL and cloud-based platforms. Brush up on your knowledge of interpretable AI techniques and be ready to discuss how you've operationalised non-technical ideas into research designs and model outputs.