Big Data Scientist
The Big Data Scientist
will be responsible for conducting statistical analysis of unique newly created financial monitoring system within Anti Money Laundering program in Citi. He/she will work with global team across the globe and execute complex statistical analysis, e.g. segmentation, and discover and classify patterns of money flows. This is an opportunity to work in a Big Data environment
, have a chance to create and implement a new project
in Citi, and practice your English on everyday basis.
This position requires ability to execute complex statistical analyses, data visualizations and algorithm simulations. Strong background in statistical techniques such as parameters estimation and hypothesis testing is required. Requirements include programming experience with data analysis, data processing and statistical tools (R/SAS, Oracle, Big Data as an advantage). Fluency in English and very good written and verbal communication skills are necessary. Key Responsibilities:
- Conduct data-driven analyses and reports; apply qualitative and quantitative data analysis methods; prepare statistical and non-statistical data exploration
- Apply statistical methods to organize, analyze, and interpret data related to AML monitoring scenarios and thresholds. Ensure appropriate methodology is selected to answer specific business questions on effectiveness of coverage
- Build and implement models and algorithms. Maintain high quality code and documentation. Assure efficiency, stability and scalability of the solution
- Detect data anomalies and identify source of data problems. Recommend data quality solutions.
- Use visualization techniques to display data and the results of analysis in clear presentations that can be understood by non-technical readers
- Design statistically valid samples, design and conduct statistical experiments. Perform statistical inference and draw conclusions from sample data
- Ensure Data Quality and Reliability. Design and implement various Data Quality methods in SAS and Big Data. Run quality checks against database and report all data issues. Detect data anomalies and identify source of data problems. Recommend data quality solutions
- Provide technical support to the team by implementing automation tools and integrating MS Office Excel, Oracle Database, SAS and Big Data platforms. Design technical solutions supporting complex data reporting and analytical tasks. Generate complex graphical data reports, including data crosstabs, scatter plots and statistical measures.
- Master degree in technical science/mathematics/statistics/quantitative methods (degree in economics/banking may be considered if strong analytical skills proved)
- 3+ years of experience in data mining methods and their application in business practice (PhD degree may be considered for the fulfilment of work experience requirements)
- 3+ years of experience with relational databases such as Oracle, SQL Server, and Data Marts/Data Warehouses, Big Data as an advantage
- Strong programming and statistical/data analytical skills (R, SAS 4GL, SQL,Python); 3+ years of experience with R or SAS
- Experience in providing the results of analyses in clear written form and presenting the findings to the audience
- Initiative, creativity and attention to details
- Ability to discuss reasoning, critical assessment of facts and opinions
- Demonstrated ability to communicate effectively, both orally and in writing
- Self-motivated with high desire of self-development and learning
- Experience in a large corporation, preferably multicultural environment
- Fluent English
- Opportunity to work and develop in an international environment in one of the greatest financial institutions worldwide
- Learning opportunities and challenging assignments in which you can utilize your knowledge
- Competitive salary and social benefits (medical care, Benefit System, life insurance and other)
- Excellent working environment
Grade :All Job Level - All Job FunctionsAll Job Level - All Job Functions - PL ------------------------------------------------------
Time Type :Full time ------------------------------------------------------
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