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- Tasks: Streamline and automate classification data delivery using cutting-edge technologies.
- Company: Bloomberg, a leader in data-driven technology solutions.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Join a dynamic team with a focus on innovation and collaboration.
- Why this job: Transform manual processes into automated workflows and make a real impact.
- Qualifications: 4+ years of Python experience and knowledge of AI/ML concepts.
The predicted salary is between 60000 - 80000 £ per year.
Location: London
Business Area: Data
Ref #: 10051370
Description & Requirements
Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock – from around the world. In Data, we are responsible for delivering this data, news and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes.
Our Team
The Classifications team builds and maintains the taxonomies that group companies and securities by business activities and risk profiles. These classifications form the foundation for peer group analysis, benchmarking, and market trend evaluation. When clients compare investment opportunities, evaluate sector exposures, or analyze historical performance, classification data provides the consistent framework that makes these insights possible.
We enable clients to:
- Assess how global, regional, or local industry trends affect portfolios
- Compare and report on sector exposures versus peers and benchmarks
- Identify investment opportunities across developed and emerging markets
- Analyze sector and industry contributions to portfolio performance
- Build consistently defined, sector-based investment and rotation strategies
What’s the role?
As a Classifications Automation Engineer, you will be responsible for streamlining and scaling the delivery of classification data across asset types by designing and implementing automated workflows. You will partner with stakeholders to identify inefficiencies, apply modern technologies (including AI/ML where appropriate), and build solutions that improve data accuracy, consistency, and timeliness. You will play a key role in transforming manual or semi-manual processes into robust, automated pipelines while developing business intelligence to monitor performance and outcomes.
We’ll trust you to:
- Analyze and optimize existing workflows, identifying opportunities for automation and scalability
- Design, build, and maintain automated data pipelines and tools to improve efficiency and accuracy
- Evaluate and apply AI/ML/NLP techniques to enhance classification processes and decision-making
- Partner with Data, Engineering, Product, and Business teams to deliver scalable solutions
- Develop metrics and monitoring to ensure data quality, timeliness, and operational performance
- Understand financial datasets and client use cases to inform automation priorities
You’ll need to have:
- 4+ years of Python programming and scripting in a production environment
- Experience building or maintaining automated workflows, pipelines, or data systems
- Knowledge of Artificial Intelligence (AI), Natural Language Processing (NLP), or Machine Learning (ML) concepts
- Strong analytical thinking and problem-solving skills with attention to detail
- Effective communication and collaboration skills across technical and non-technical teams
- Adaptability and a proactive approach to driving change and improvement
We’d love to see:
- Experience with Agile development methodologies (e.g., Scrum)
- Familiarity with the Bloomberg Terminal
- Knowledge of financial markets and instruments
- Experience with data visualization or BI tools such as Tableau or Qlik Sense
Does this sound like you? If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email amer_recruit@bloomberg.net
Senior Data Management Professional - Automation Engineer - Classifications London, GBR Posted today employer: Bloomberg L.P.
Contact Detail:
Bloomberg L.P. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Management Professional - Automation Engineer - Classifications London, GBR Posted today
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving automation and data management. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to automation and data workflows. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Senior Data Management Professional - Automation Engineer - Classifications London, GBR Posted today
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python programming, automation experience, and any relevant AI/ML projects you've worked on. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data management and automation. Share specific examples of how you've improved workflows in the past. Let us know why you're the perfect fit for this role!
Showcase Your Problem-Solving Skills: In your application, don't just list your skills—demonstrate them! Share stories of how you've tackled challenges in previous roles, especially those related to data accuracy and efficiency. We love seeing innovative thinkers!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Bloomberg L.P.
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of financial datasets relevant to the role. Brush up on how classification data impacts investment decisions and be ready to discuss specific examples of how you've used data to drive insights.
✨Showcase Your Automation Skills
Prepare to talk about your experience with building automated workflows and pipelines. Bring examples of past projects where you’ve successfully implemented automation, especially using Python or AI/ML techniques, to demonstrate your hands-on expertise.
✨Communicate Clearly and Collaboratively
Since this role involves partnering with various teams, practice explaining complex technical concepts in simple terms. Highlight your collaboration experiences and how you’ve worked with both technical and non-technical stakeholders to achieve common goals.
✨Be Ready for Problem-Solving Scenarios
Expect to tackle some real-world problems during the interview. Prepare by thinking through potential inefficiencies in data workflows and how you would approach automating them. This will showcase your analytical thinking and problem-solving skills.