Global Data Manager - Data Science
Posted Jun 21, 2019 - Requisition No. 75728
Bloomberg runs on data, and in the Global Data team we're responsible for acquiring it and providing it to our clients. We collect, analyse, process and publish the data which is the backbone of our iconic Bloomberg Terminal- the facts and figures which ultimately move the financial markets. We apply problem-solving skills to identify innovative workflow efficiencies and we implement technology solutions to enhance our systems, products and processes- and all this while providing platinum customer support to our clients.
What’s the role?
Bloomberg is looking for a skilled data scientist to be based in our London office to solve complex, tangible day to day business questions leading to extending Bloomberg's core businesses.
In this exciting role, you will design, create, implement, and manage analytics that leverage large and varied datasets, both financial and non-financial, using a wide range of analytical tools, methods and platforms. You will be leading projects where your interests and enthusiasm will have a major impact on business direction.
As the technical lead for a number of data scientists, you will be responsible for identifying appropriate data models, devising methods of instrumenting our system to extract this information and appropriate artefacts to enable the development of business insights.
You will be expected to identify areas of interest to the business, recognise which models and concepts should be applied to the business problem and acquire the data resources. You will create and implement those models. An open, creative approach is critical to your success. Alongside this you will be a partner and stakeholder to engineering and CTO teams responsible for the technology stack and its components, ensuring adoption, standards and governance throughout projects.
You will design lean proofs of concepts (POC) to answer targeted business questions, explore and work with a wide range of proprietary, interesting data stores and apply existing methods or develop new methods. You will also engage in data analysis in a practical way, convince business leaders that your results are worth investing in and educate other analysts and business team members.
Most critically, you will deliver the output of your analyses to business users (both non-technical and technical). You will be the point person to answer questions about the workflow and interactions and you will help shape critical customer experiences with Bloomberg's products.
Types of projects for a typical week could include:
- Entity recognition and linking across multiple languages to enhance data acquisition and processing automatically
- Information extraction from unstructured or semi-structured text for real time automated news insights
- News, Filings and Exchange based document classification and routing across multiple asset classes
- Providing Bloomberg senior management with predictive analytics to improve forecasting.
- Experience with mapping business needs to a data science solution
- Substantial experience with the use of relational databases for data storage
- Experience using SQL for data extraction and management (MSSQL, Oracle, MySQL)
- Knowledge of NoSQL data stores, MapReduce and software frameworks like Hadoop
- Must be able to address multiple priorities in an extremely fast-paced environment
You’ll need to have:
- Proven experience in the use of advanced statistical analysis for data analysis (e.g. descriptive statistics, statistical significance, statistical population/model, etc.)
- Proven experience in the use of machine learning to solve real world problems (e.g supervised/unsupervised learning, natural language processing)
- Expertise in numerical and visualization toolkit (e.g. R, SAS, Python, MatLab, madlib, etc.)
- Advanced expertise in SQL is a requirement for this role. Expertise with PostgreSQL /Greenplum required
- Experience with HDFS - HaDoop FileSystem
- Superior ability to break down large, complex business problems into discrete, achievable steps
- Ability to clearly communicate research findings to both technical and non-technical decision makers
- Experience with Excel
- Experience with presentation software
- Experience testing and validating statistical hypotheses
- A degree in Statistics, Maths, Computer Science, Engineering, Physical Sciences, or another quantitative discipline is a plus
- Web Analytics a plus
Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are! In the meantime feel free to have a look at this:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status
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