S&P Global Full Stack Engineer - Data Science in New York, New York
The Data science team is a newly formed applied research & software engineering team within S&P Global Ratings that will be responsible for building and executing a bold vision around using Machine Learning, Natural Language Processing, Data Science, knowledge engineering, and human computer interfaces for augmenting various business processes.
This role will have a significant impact on the success of our data science projects, delivering the highest quality software and data engineered solutions, ultimately enabling and augmenting our business processes and products with AI and Data Science capabilities.
What s in it for you
This is a high visibility team with an opportunity to make a very meaningful impact on the future direction of the company. You will work with senior members of the team to help define, design and build the systems. You will work closely with other senior technical staff across the company to create state of the art user interfaces - experiences and engineering solutions that will integrate with Augmented Intelligence, Data Science and Machine Learning based back-end services.
As a Full Stack Engineer you will be responsible for building user interface and server-side components, and their integrations with databases and cloud based back-end services. You will need to rapidly prototype various UI components and back-end services and test their efficacy using appropriate testing and validation processes, and iteratively enhance the system to be robust and scalable.
BS in Computer Science or Engineering with 5-8 years of relevant industry experience.
Experience programming in a high-level language (e.g. Java, Scala, Python)
Experience with distributed computing platforms, such as Hadoop (Hive, HBase, Pig) and Spark
Understanding of RESTful APIs, and integration experience with databases (SQL and NoSQL, Oracle, MySQL, Cassandra, MongoDB)
Experience writing unit and functional tests and using testing frameworks
Experience working with cloud based managed services such as Amazon EMR, RDS, S3, etc
Comfortable with Linux, dependency management, build, CI - CD and DevOps tools
Integration experience with information retrieval and search engines, e.g. Solr - Lucene
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