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.
- 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
- 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
About the company
Citi works tirelessly to provide consumers, corporations, governments and institutions with a broad range of financial services and products. We strive to create the best outcomes for our clients and customers with financial ingenuity that leads to solutions that are simple, creative and responsible.