S&P Global Associate Director, Senior Data Scientist in New York, New York
The Data Science team is part of Technology in the S&P Global Market Intelligence. The Data Science team works closely with business stakeholders and divisions to develop cutting-edge data science solutions that enhance our products and services and streamline our operations using machine learning, data engineering, and Visual Analytics,
In this role, you will have the opportunity to work on a diverse cutting-edge of data science projects that utilize machine learning and AI to enhance our products, streamline our businesses and operations, and open new market opportunities.
What s in it for you:
S&P Global is a Fortune 500 company and a recognized industry-leading provider of data, analytics and market insight. We provide a data-rich environment and various opportunities to have a lasting impact in data science applications to finance and analytics.This is an opportunity to use your data science skills to change the direction of the company. You will work with data science and technology leaders in the company.
Design, develop, and deploy data science projects aimed at solving high-impact business problems using machine learning, natural language processing, and related data science techniques
- Implement data science project within the data science lifecycle of development including data preparation, data analysis and modeling,evaluation - interpretationof results and presentation to leaders.
Deliver the data science solution in the form tool, software assets, or report.
Be proactive in the identification data science project opportunities and making the case of data science solutions
Interact with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements for solutions
Accurately communicate the vision and status of your data science projects to data science leaders, while meeting business expectations.
- Basic Qualifications:*
BS in Math, Statistics, Computer Science, Engineering, Operation Research, or related fields with 7 years of relevant industry experience
o MS in Math, Statistics, Computer Science, Engineering, Operation Research or related fields with 4 years of relevant industry experience
o Experience in one or more of the following areas:*
Machine learning, Statistics, Natural Language Processing, Speech to Text systems, Computer Vision, Information Retrieval, Recommender Systems, and related fields.
o Proficient programming skills in Python or R. Optionally, Scalia, Perl, Java, C - C ,o Experience with statistical data analysis, experimental design, and hypotheses validation o Experience with some standard machine learning platforms (e.g., Scikit-learn, tensorflow, pytorch, Caffee, and similar)
o A plus:*
o Experience with NLP platform (word2vec, Stanford NLP, OpenNLP, Gate, Spacy, and similar)
o Working knowledge of traditional data storage, relational databases, SQL, and ETL tools
o Exposure to Big Data platform and distributed computing such as Hadoop ecosystem (Hive, HBase, Pig) and Spark
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.
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.
The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law.