Quantitative Data Engineer
At Bloomberg, our product is our data. The Global Data department is the core of Bloomberg's product offering, providing our Terminal and Enterprise clients with the data that powers decision making throughout the financial industry. We combine deep product knowledge with the latest technology to define what it means to be a modern financial data provider.
We see the impact of our work every day, whether it's building pipelines to process financial data, designing systems that drive decision-making, or finding ways for our colleagues to more easily do their jobs. We get to work with market data to resolve anomaly detection, assess the quality of data feeds to evaluate the accuracy of forecasts, and figure out how to best combine system automation with a human touch, bringing value to our businesses and ultimately to our clients. What's the role?
In Global Data's Technical Operations team (GDTO), we build automated systems that handle the huge variety of data that Bloomberg delivers to customers worldwide. The latest developments in the space of data analytics and machine learning are resulting in an increased number of opportunities to automate data processes and derive new content. In order to continue to meet a growing demand for solutions based on algorithmic data processing and quantitative decision making, our London based group is searching for analytical data engineers to join the team. Successful candidates will be able to validate conceptual hypotheses through quantitative data-driven assessment, as well as transform a proof-of-concept into a production solution used in Bloomberg's day-to-day operations.
As a Quantitative Data Engineer in GDTO, you'll be working with a group of hardworking colleagues to research, build and deliver solutions to data management challenges across our department, through means of data analysis and algorithmic design. You'll be working on projects that directly support the wide range of products managed by Global Data, as well as broader initiatives that are at the core of data management standard methodologies, such as data quality, to leverage synergies across products. We're looking for someone that is able to understand business needs, perform hands-on analysis on available data, design and prototype ideas, evaluate alternatives, reach conclusions, build solutions and pipelines, and monitor results. We'll trust you to:
A successful candidate will have a strong combination of the following:
- Use your analytical experience to automate data management processes by designing, developing and deploying novel ML pipelines
- Become a leading specialist in our ML/NLP stack, identify strategic development opportunities, and advocate for scalable and long-term solutions over short-term workarounds
- Own the end-to-end delivery of projects, from identifying the initial ideas, acquiring and exploring the data to fitting statistical models and integrating/deploying these into production pipelines, while working effectively with counterparts in your immediate team and across the department
- Promote data-driven decision making, by validating hypotheses using business intelligence data, and challenging the obvious answers to discover the underlying causes of observed patterns
- Guide and mentor peers in your area of responsibility and subject matter expertise
Does this sound like you?
- Advanced degree in Computer Science, Mathematics, or relevant data technology field and/or professional work experience in software development, data engineering, data science, or machine learning
- Advanced ML/NLP/quantitative analytical development experience, designing software architecture and building production-grade applications, using primarily Python-based industry-standard toolkits to solve real-world data management problems; tasks might include cluster analysis, time-series analysis/forecasting, automated quality control, paragraph/document classification, data point extraction and subjective interpretation of non-numeric data from noisy unstructured text (e.g. topic modelling)
- Applied Python development experience with awareness of the latest trends in the development workflow, testing and quality
- Experience with working on complex long-term projects, involving multiple partners and changing requirements
- Ability to identify trends and patterns in data, spot gaps and seize opportunities that challenge the status quo
- Ability to establish and maintain strong networks across an organisation
- A proactive self-starter approach and a great collaborative attitude, with an ability to spot complementary strengths across people working together
- Excellent written and verbal communication skills, especially when conveying compelling stories of technical complexities to an audience with a wide range of domain knowledge
Apply if you think we're a good match! We'll get in touch to let you know what the next steps are.
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