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. Preferred Qualifications:
- 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)
At S&P Global, we don't give you intelligence-we give you essential intelligence. The essential intelligence you need to make decisions with conviction. We're the world's foremost provider of ratings, benchmarks and analytics in the global capital and commodity markets. Our divisions include:
- S&P Global Ratings, which provides credit ratings, research and insights essential to driving growth and transparency.
- S&P Global Market Intelligence, which provides insights into companies, markets and data so that business and financial decisions can be made with conviction.
- S&P Dow Jones Indices, the world's largest resource for iconic and innovative indices, which helps investors pinpoint global opportunities.
- S&P Global Platts, which equips customers to identify and seize opportunities in energy and commodities, stimulating business growth and market transparency.
To all recruitment agencies: S&P Global does not accept unsolicited agency resumes. Please do not forward such resumes to any S&P Global employee, office location or website. S&P Global will not be responsible for any fees related to such resumes.
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.
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