• Competitive
  • Hong Kong
  • Permanent, Full time
  • Citi
  • 22 Nov 17

HK - GCB - Senior BigData Modeler

HK - GCB - Senior BigData Modeler

  • Primary Location: HK,Hong Kong,Hong Kong
  • Education: Master's Degree
  • Job Function: Operations Credit Ops
  • Schedule: Full-time
  • Shift: Day Job
  • Employee Status: Regular
  • Travel Time: Yes, 10 % of the Time
  • Job ID: 17068506


Description

  • Work with a small but focused BigData analytics team to conduct data mining in Hadoop ecosystem across a big variety of large datasets, understand fraud / risk elements and pattern, and design corresponding analytical solution
  • Research and develop machine learning / deep learning models on banking transactional data, staff behavioral data, and more importantly, on Natural Language Process and Image Processing domain to deliver state-of-the-art surveillance solution to the franchise
  • Be responsible for UAT testing, MIS reporting and documenting the solution designed to meet the risk and process control standard of Citi
  • Be responsible for knowledge transferring, coaching on advanced analytics and generalize the solution to all the regional internal fraud teams within Citi via liaising with corresponding stakeholders across the globe
  • Be partner with technology function in Citi for data management including new data acquisition, data model design, and data quality investigation in Hadoop ecosystem


Qualifications

  • Prefer Master / PhD in Mathematics / Statistics / Computer Science / Engineering / Any other major that is able to demonstrate solid technical and analytical skills
  • 2+ years' working/research experience in data mining / machine learning
  • Experience on Fraud/Anomaly Detection / Risk Management is a plus
  • Proficient in data query language: SQL or NoSQL. Experience on Hive/Pig is a plus
  • Proficient in using R to conduct data mining, modeling; Python proficiency is a plus
  • Basic data mining techniques - principle component analysis, factor analysis, hypothesis testing, clustering etc.
  • Basic Text Mining - tokenization, lemmatization, parsing, semantic analysis; Knowledge on Natural Language Processing / Image Processing is a plus
  • Knowledge and project experience on supervised machine learning models - Regression, Logistic, Neural Network, SVM, Bayesian Network; Un-supervised machine learning models - Nearest neighbor, K-means. Knowledge on Deep Learning is a plus
  • Proficient in both spoken and written English. Fluency in other languages is a plus
  • Focused and proactive; Open-minded and creative; Matured and teamwork
  • Be ready for and willing to travel or short-term oversea assignment