• Negotiable
  • London, England, United Kingdom
  • Permanent, Full time
  • Standard Chartered Bank
  • 10 Oct 17

Machine Learning Quant, Group Finance

  • Location: London, England, United Kingdom
  • Salary: Negotiable
  • Job Type: Full time

Please view Job Description for details.

Machine Learning Quant to support the development of predictive models for Stress Testing and Corporate Plan
SCB's Quantitative Modelling and Analytics team is responsible for the research, development and implementation of quantitative models (particularly PPNR models) and visual analytic tools. The scope of the work covers areas such as Retail, Transaction Banking, Corporate and Investments Banking (CIB) products as well as areas such as commodities, interest rates and FX. The outputs are used for:
  • Stress Tests
  • Capital and Liquidity Management (CLM)
  • Financial Planning & Analytics (FP&A)
The role holder will be responsible for development, validation and documentation of quantitative models for Stress Testing and Corporate Plan in a way that meets regulatory guidance and internal requirements, managing the development through to final approval.

Key Roles and Responsibilities

Machine Learning Models (60%):
  • Experience in developing scripts to programmatically source, clean, aggregate/disaggregate, transform raw data for quantitative modelling (primarily in R and Java).
  • Develop new regulatory and business-related models using Generalized Additive Models framework and other machine learning techniques.
  • Provide robust model selection, testing and validation methodologies.
  • Document new models to the Group standards and best industry practice, prepare submission for independent model validation
Visual Analytics (20%):
  • Develop interactive visualisations to empower business users to explore and understand model outputs (e.g., R Shiny).
  • Develop visual exploratory analysis processes in ways that work in harmony with socialisation of quantitative models and development of 'data-driven storytelling'.
  • Communicate important trends and patterns.
Stakeholder Management (20%):
  • Ability to work well within a team of machine learning and quantitative modellers, analyst and business experts, with a desire to take initiatives in the specification and development of solutions.
  • Ability to meet deadlines and work under tight time scales.
  • Be flexible and able to switch from visual analytics to quantitative modelling following stakeholders' feedback
  • Good verbal and written communication skills, including presentation skills.
  • Interpersonal skills appropriate for communication within Standard Chartered Bank, external stakeholders and with the wider financial and banking community.

Qualifications and Skills

  • Post graduate degree (preferably PhD) in Statistics, Data Science and/or related discipline with a strong programming experience in R and Java.
  • Advanced programming in R and Java with proven experience in developing re-useable scripts to enhance team productivity.
  • Good knowledge of machine learning and computational statistics, e.g. regression analysis, time-series analysis, smoothing techniques, random forests, gradient boosting machines.
  • Track record of producing high quality development code and documentation including results of research and presentations for technical and non-technical audiences

Diversity and Inclusion

Standard Chartered is committed to diversity and inclusion. We believe that a work environment which embraces diversity will enable us to get the best out of the broadest spectrum of people to sustain strong business performance and competitive advantage. By building an inclusive culture, each employee can develop a sense of belonging, and have the opportunity to maximise their personal potential.