Job Purpose:
As an integral part of the Enterprise Supply Chain framework, ESC Analytics is responsible for reporting and analysis on the end-to-end supply chain operations within Citigroup on a global basis. Within that the Data Science Team works with big data technologies to develop predictive capabilities and understand supplier, business behaviors to support the ESC Functions, and various Citi Businesses that use third parties in their supply chains.
This role will focus on the research, optimization and execution of machine learning algorithms within the p2p process of the Enterprise Supply Chain and drive a deep behavioral understanding and analysis of the overall supply chain. Experience in problem solving, including developing machine learning experiments for statistical inference on complex business processes, develop deep learning architectures for pattern recognition and optimization to formulate strategic business recommendations.

Primary Responsibilities:
Statistical Analysis: Analyze integrity and structure of data sets to develop data appropriate machine learning models (Random Forest, Markov Models, Association Rules Mining, SVM, GBM, etc...) and use appropriate model evaluation techniques ( confusion matrix, ROC curve, cross validation, etc...) for algorithm development.
Data Modeling: Design and build efficient, flexible and sustainable data and statistical models with statistical scripting language (R, Python, SAS) to run necessary machine learning experiments and optimization research within a Hadoop framework. Strong feature engineering acumen.
Research and Production: Carry out critical research of current and future concepts of machine learning to internally experiment and drive new applicable innovative techniques within a non-traditional procurement space. Understand strengths and weakness of the data and have the ability to operate in the “grey” and make logically sound decisions with supported research
Business Analysis: Interface with ESC business units to understand underlying business drivers for data acquisition, ETL and machine learning modeling
Analysis: Provide analytic insights on model training, performance and enhancement, and analytics across Citi geographies and businesses to drive strategic business planning
Visualizations: Develop comprehensive visualizations that supports and grow a data culture within the organization. Bring to the forefront process and expense opportunities to assist with strategic conversations through compelling visualizations

Qualifications:
BS degree in Computer Science, Mathematics, Statistics or Engineering required
Master's degree in Mathematics or Statistics highly preferred
2 years of relevant work experience or internships preferred

Knowledge/Experience:
Strong statistical and mathematical background with knowledge of supervised and un-supervised machine learning methods
Strong coding skills with a statistical scripting language such as R, Python and or SAS;
Strong problem solving acumen with ability to breakdown complex problems, specifically feature engineering knowledge for model development
Prior experience and knowledge of working within a Hadoop framework and big data technologies such as Sparklyr and HUE
Highly motivated self-starter that takes initiative and has the ability to effectively organize, multi-task and prioritize a wide array of projects;
Prior experience working in a global team environment preferred, but not required;
Procurement, Risk and Operational knowledge preferred, but not required;

Skills:
Excellent communication skills with the ability to interface with technical and non-technical audience and work well in a team environment;
Strong technical knowledge using big data tools and techniques to breakdown complex data problems and create robust data models;
Strong business analysis skills to include problem solving, decision making, relationship building and management, detail oriented, documentation management;
Strong financial analytics knowledge to support insight analysis with the information available;
Ability to work with data from many different sources to build a logical data flow to support data modeling
Analytical and statistical skills with the ability to recognize data patterns, work of data intuition and continuously ask “why”;
Strategic problem solving and opportunity identification;
Advanced communication/presentation skills as well as the ability to collect and share constructive feedback;
Possess cross-cultural and cross-functional collaboration skills
Strong work ethic, good attitude and team player

-

Grade : All Job Level - All Job FunctionsAll Job Level - All Job Functions - US
-

Time Type : Full time
-

Citi is an equal opportunity and affirmative action employer.
Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity.

Citigroup Inc. and its subsidiaries ("Citi”) invite all qualified interested applicants to apply for career opportunities. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity CLICK HERE.

To view the "EEO is the Law" poster CLICK HERE. To view the EEO is the Law Supplement CLICK HERE.
To view the EEO Policy Statement CLICK HERE.
To view the Pay Transparency Posting CLICK HERE.