Client Algo Quantitative, VP

  • Purpose of Role: As part of State Street's EFX business expansion plan, this role involves generating and researching ideas to expand our client algo execution offering, enhance customer experience, as well as working closely with different trading teams to promote internalisation.

    Major Responsibilities:

    • Involve in the full life cycle of algo product development. Generating new ideas, identifying performance improvements and control gaps, specifying, developing, backtesting and prototyping quant models, performing liquidity analysis and provisioning, working closely with IT development team, business risk, compliance and model validation team
    • Provide 2nd level support to address clients' questions and perform bespoke analysis as required.
    • Work with sales and meet with clients to understand algo requirements
    • Develop pre-trade and market liquidity analytics tool
    • Analyze and optimize algo flow and behavior to improve performance and customer experience
    • Display a culture of individual ownership of tasks to embed a clear individual sense of accountability in performing the role
    • Display the highest level of the Code of Conduct and support the 'Risk Excellence' culture within the business.
      Level of Education/ Qualifications:
      Postgraduate degree (PhD or Masters) in Mathematics, Data Analytics, Machine Learning, Statistics or related field.
      Skills and Experience
    • Experience and solid knowledge in efx market and developing fx algos
    • Excellent interpersonal skills to communicate clearly with traders, sales, clients and able to go into details when working with IT
    • Object oriented programming skills: Java or C++
    • Proficiency in statistical packages such as Matlab, Python or R
    • Strong statistical foundations and experience in analysing large data sets and tick data Required Competencies
    • Pragmatic mindset - research should be targeted at solving business problems and improving profitability
    • Self-motivated and with ability to work and add value with minimal supervision