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AVP - Data Science Team (Analytics Team)

Job Req ID 22591188 Location(s) Singapore, Singapore Job Category Decision Management
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Institutional Credit Management (ICM) works closely with our Institutional Client Group (ICG) business partners to serve as a critical component of our First Line of defence (FLOD) for wholesale and counterparty credit risk management. ICM is an ‘in business’ credit management function. A critical component of ICM is the delivery of technical / analytical capabilities to support the delivery of; Portfolio level monitoring, Limit setting / monitoring and operational review / disposition of arising credit risk indicators. Portfolio Management Infrastructure & Analytics (PMIA) is the entity in ICM responsible for designing, building, delivering and maintaining such technical / analytic capabilities, in a globally common, flexible and comprehensive data centric manner.

ICM is a function established within the last 12 months and is in the ‘build’ / ‘transform’ stage of operations. A lot of the work effort is new build work. This requires significant research and fact finding to support to design of the appropriate end state solution blending the routine with ‘bleeding edge’ analytics delivered through an in business  ‘dev/ops’ approach. Resourcing will be aligned to and focused on Citi’s internal ‘Big Data’ ecosystem components, being; Data, (sourcing, engineering, quality, provisioning), Analytics (linear objective conditions, feature creation, anomaly detection, machine learning {in time} and holistic thematic focused statistical analysis / presentation) and Platform (the engagement with Technology teams to deploy the optimal platform to support the needs of the business. An abject focus on ‘controls’ across all aspects will be tantamount to success as will the satisfaction of regulatory requirements / expectations. The single critical overarching intent though is to deliver value ICM and the wider ICG business.

PMIA, as a function, is structured to have three vertical: Data, Analytics and Controls. This position will lead the Analytics function with the below Key responsibilities, reporting to the global PMIA lead.

Key Responsibilities

As a member of the Data Analytics team you will be responsible for:

  • Proactively contributing to and supporting in the design, coding and deployment of a variety of analytic capabilities on structured and unstructured data.
  • Supporting the team leader, as a core data scientist, in the interpretation / realisation of business requests through the coding and creation of statistically focused data driven routines.
  • Exploration of existing / new data sets to facilitate the proactive identification of Credit Risk events.
  • Support the satisfaction of various Citi policy requirements, in particular the Models Risk Management policy with supporting documentation and data assessments.
  • Proactively engage in outreach to different business partners to dimension and understand requirement, with detailed knowledge of data availability, and work together to conduct data investigation / analytic solutioning.
  • Working as a team member collaboratively to support data simulation and hypothesis proofing of analytic routines.
  • Engage with and partner the data team on data; discovery, investigation, integration, design, indexing, engineering to support application of advanced analytics. Code ‘code’ in appropriate language to deliver to the ideated analytic routines to support the proactive identification of credit risk events, on structured and unstructured data.
  • Fulfil a key role in a ‘dev/ops’ team of data scientists to ensure optimally coded routines are made available to users / technology to support production / sandbox deployments, critically as a partner with Tech teams.
  • Drive an aggressive agenda for real time visualisation of data sets and analytic outputs.
  • Satisfy the integrated control expectations of all relevant Citi policies and particularly those related to Data and Models risk management.
  • Work as an SME and contribute to more strategic data initiatives across the firm helping to shape and influence a more collaborative ‘data agenda’.
  • Optimise the use of a decentralised team to ensure timely product delivery across multiple time zones.

Expected Experience

  • Proven experience of contributing to a data focused analytic capability in a multinational financial (preferable) regulated institute.
  • 4-6 years of deep analytic focused work product leveraging Distributed File System ecosystem tools; Linux, Python, Spark, Hive, Hue, No Sql etc. (Exceptional Office product capabilities are assumed.)
  • Proven intellectual competency / curiosity to explore data to create code to proactively predict / identify credit risk indicators.
  • Experience of proactive business outreach / communication to competently source support and recognition of the value added.
  • Proven ‘coding’ capability to support working in a forward thinking ‘dev/ops’ team.
  • Intricate understanding of data; indexing, model, quantification, quality and assessment / reporting.
  • Proven capability of data science. (Advanced ‘office’ suite applications is a given.)
  • Exceptional time / project management / coordination across multiple stakeholder groups and the proven adoption of a ‘leadership’ role in resolving arising issues.
  • A demonstrated acceptance of accountability for tasks undertaken.
  • Exceptionally high standards are a given expectation.
  • Experience of strategic ‘data’ engagement beyond pure analytics and demonstrated awareness of ‘industry data’ considerations.


  • Critical, but creative, thinker and an ability to ‘translate’ work / product to non data analytic individuals.
  • Exceptional communication skills and a passion for advocating data science
  • An energetic and solution focused individual prepared to navigate multiple policies / procedures to deliver bleeding edge solutions creating followership and influence to achieve new build environments.
  • Desire to excel in a new fast moving data centric work environment primarily focused on building as opposed to running.


Numerate BSc focused undergrad. Preferable; Msc with a data / data science / data engineering analytic focus.


Job Family Group:

Decision Management


Job Family:

Specialized Analytics (Data Science/Computational Statistics)


Time Type:

Full time


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