The Global Data Technology and Operations team is looking for someone who has practical skills and a passion for applying empirical research. Someone who is experienced in using data driven insights and predictive models to discover information that may be used to solve complex business questions and create opportunities that enhance and extend the firm’s franchise.
This unique role will have you engaged in the design, creation, implementation, and management of predictive 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 joining a small team where your interests and enthusiasm will have a major impact on business direction.
As we continue to expand and enhance our data products, Bloomberg is looking for someone who has previously been responsible for investigating and using predictive analytics to build our future solutions. Flexibility in project areas, methods, and procedures is a must. This role will involve identifying areas of interest to the business, recognizing which models and concepts should be applied to them, and then acquiring the necessary data resources and creating and implementing those models. An open approach and desire to help cultivate the use of predictive modeling within the firm is essential.
– Research, develop and implement new methods of measuring and analyzing data sets and processes.
– Work with a range of proprietary, industry standard, and open source data stores to assemble and organize and analyze data.
– Design models to answer targeted business questions and engage in data analysis at the highest level.
– Educate other analysts and business team members to expand impact to additional products or business units.
– Construct and present research ideas, prototypes and proofs of concepts.
– Advanced Degree in Statistics, Math, Engineering, Physical Sciences, Computer Science or another quantitative discipline.
– 5+ years work experience in the use of advanced statistical analysis/machine learning methods in data analysis and decision making.
– Experience with mapping business needs to engineering systems.
– Fluent in modern advanced analytical tools (e.g. Python, R, MATLAB etc.).
– Substantial experience with the use of relational databases for data storage and analysis including fluency with using SQL for data extraction and management (MSSQL, Oracle, MySQL, postgresql etc.).
– Knowledge of NoSQL data stores, MapReduce and software frameworks like Hadoop.
– Must be able to address multiple priorities in an extremely fast-paced environment.
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