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Data Scientist - CTO Data Science
  • Python
  • Spark
  • Machine Learning
  • Modeling
  • Hadoop
Bloomberg
New York, NY
130 days ago

Who we are:

The Bloomberg CTO Office is the future-looking technical arm of Bloomberg L.P. We envision, design and prototype the next generation infrastructure, hardware and applications that interface in all aspects of the company including financial products, broadcast and media, data centers, internal IT and our global network. We are passionate about what we do.

What we do:
The CTO Data Science department is a dynamic, collaborative and intellectually stimulating environment - the work is always exciting and the problems we tackle are never boring. From this department we guide the company's overall strategic direction for machine learning, natural language processing, and search throughout the entire business. We are transforming our business through these technologies as well as the insights we provide our customers across the global financial sector.

At Bloomberg, our systems ingest hundreds of billions of market data ticks and millions of curated news stories for financial players to process and make investment decisions. The CTO Data Science department's machine learning efforts enhance our clients' ability to find the right pieces of information that are necessary to succeed in their jobs.

What’s in it for you:

You will be part of a newly formed team within the CTO Data Science department at Bloomberg. You will be working alongside world-class talent to find innovative solutions to some of the most interesting problems in the Financial Industry. You will be responsible for diving deep into data sets to understand their structure, health, and relevance to extract all the stories that data can tell. You will work closely with others in the CTO office, Engineering, the Quantitative Research group and the Product organization to learn about problems our clients face and to develop cutting edge analytics and deliver new data products.

You’ll need to have:

  • 3+ years of work experience in the use of advanced statistical analysis and machine learning methods (e.g. topic modeling, neural networks, ensemble models, SVM, random forest, linear regression, statistical significance, correlation, to name just a few…)
  • Expertise understanding and working with multiple file types, schemas and data types.
  • Experience with HDFS and Analytics on Hadoop (HIVE/SPARK).
  • Superior ability to break down large, complex business problems into discrete, achievable steps.
  • Ability to clearly communicate research findings to technical and nontechnical clients.
  • Experience testing and validating statistical hypotheses.
  • Expertise in statistical, numerical and visualization toolkit in R or Python (preferred).
  • Degree in Economics, Finance, Statistics, Math, Computer Science, Engineering, Physical Sciences, or another quantitative field is highly desirable. Advanced degree preferred.

We’d like to see:

  • Ability to tackle loosely defined problems and a strong disposition to dive deep while maintaining strategic perspective.
  • Comfortable handling multiple projects to solve varied problems working with multiple teams.
  • Empirical, independent, detail-oriented mindset.
  • Sense of ownership of his/her work, working well both independently and within a collaborative team.

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