JobDescription : The Team: The Data science team is a newly formed applied research 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.
The Impact: This role will have a significant impact on the success of our data science projects ranging from choosing which projects should be undertaken, to delivering highest quality solution, ultimately enabling our business processes and products with AI and Data Science solutions.
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 leaders in the organization to help define, build, and transform our business. You will work closely with other senior scientists to create state of the art Augmented Intelligence, Data Science and Machine Learning solutions.
Responsibilities: As a Data Scientist you will be responsible for building AI and Data Science models. You will need to rapidly prototype various algorithmic implementations and test their efficacy using appropriate experimental design and hypothesis validation.
Basic Qualifications: BS in Computer Science, Computational Linguistics, Artificial Intelligence, Statistics, or related field with 5+ years of relevant industry experience.
MS in Computer Science, Statistics, Computational Linguistics, Artificial Intelligence or related field with 3+ years of relevant industry experience.
Experience with Financial data sets, or S&P's credit ratings process is highly preferred.
Knowledge and working experience in one or more of the following areas: Natural Language Processing, Machine Learning, Question Answering, Text Mining, Information Retrieval, Distributional Semantics, Data Science, Knowledge Engineering
Proficient programming skills in a high-level language (e.g. Java, Scala, Python, C/C++, Perl, Matlab, R)
Experience with statistical data analysis, experimental design, and hypotheses validation
Project-based experience with some of the following tools:
Applied machine learning (e.g. libSVM, Shogun, Scikit-learn or similar)
Natural Language Processing (e.g., ClearTK, ScalaNLP/Breeze, ClearNLP, OpenNLP, NLTK, or similar)
Statistical data analysis and experimental design (e.g., using R, Matlab, iPython, etc.)
Information retrieval and search engines, e.g. Solr/Lucene
Distributed computing platforms, such as Hadoop (Hive, HBase, Pig), Spark, GraphLab
Databases (traditional and noSQL)
S&P Global is an equal opportunity employer committed to making all employment decisions without regard to race/ethnicity, gender, pregnancy, gender identity or expression, color, creed, religion, national origin, age, disability, marital status (including domestic partnerships and civil unions), sexual orientation, military veteran status, unemployment status, or any other basis prohibited by federal, state or local law. Only electronic job submissions will be considered for employment.
If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
Internal Number: 4800837
About S&P Global
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