World Business StrategiesServing the Global Financial Community since 2000


The presentation information for WQF Americas will be added soon.

PANEL: Talent Attraction & Retention


  • What are QR Financial Services currently doing and what should they be doing to attract more female talent?
  • What can Universities and Recruitment companies do to help?
  • What strategies are financial companies using at present if any?
  • What are QR Financial Services currently doing and what should they be doing to retain female talent?
  • What top positions besides Asset Management can QF- profiled women occupy?
  • For each position open, the percentage of female CVs submitted is very small (if not none). Why is this happening and how can universities/headhunters/companies work together to improve the numbers?
  • At more senior levels the number of women is even lower than at entry level which means that the female population retention rate is low or/and women are not being promoted. Discuss.
  • Mentoring programmes that could specifically help Diversity & Inclusion.
  • Are quantitative positions too specialised which prevents women (and men) to move horizontally to different (and possibly more senior) roles?

PANEL: Machine Learning, AI & Quantum Computing in Quantitative Finance 


  • What is the current state of utilisation of machine learning in finance?
  • What are the distinct features of machine learning problems in finance compared to other industries?
  • What are the best practices to overcome these difficulties?
  • What’s the evolution of a team using machine learning in terms of day to day operations?
  • What is a typical front office ‘Quant’ skillset going to look like in three to five years time?
  • How do we deal with model risk in machine learning case?
  • How is machine learning expected to be regulated?
  • What applications can you list among its successes?
  • How much value is it adding over and above the “classical” techniques such as linear regression, convex optimisation, etc.?
  • Do you see high-performance computing (HPC) as a major enabler of machine learning?
  • What advances in HPC have caused the most progress?
  • What do you see as the most important machine learning techniques for the future?
  • What are the main pitfalls of using Machine Learning currently in trading strategies?
  • What new insights can Machine Learning offer into the analysis of financial time series?
  • Discuss the potential of Deep Learning in algorithmic trading?
  • Do you think machine learning and HPC will transform finance 5-10 years from now?
  • If so, how do you envisage this transformation?
  • Can you anticipate any pitfalls that we should watch out for.
  • Discuss quantum computing in quant finance:
    • Breakthroughs
    • Applications
    • Future uses

PANEL: Career Progression


  • Do you think that being a woman is a significant factor in slowing down career progression in QR Financial Services?
    • If so, could this be avoided and how?
  • Discuss the Importance and value of mentorship and sponsorship
    • What mentoring programs are available for juniors if any?
  • Is it still hard to make it to the top positions, if so why and what can do done to change the situation?
  • Discuss female role models in finance and significant achievements
  • Tips from coaches on career progression (eg having your voice heard)
  • Actively managing your career; distribution of opportunity set
  • Gender diversity issues (discuss numbers, policies, how to address it)
  • Maternity leave
  • How important are the following:
    • Promotions/Career opportunities
    • Pay gap elimination
    • Agile/Flexible working
    • Getting the feedback you need (even if you don’t really want it)
    • Supporting each other
  • Discount Structure
  • 50% Academic Discount
    (FULL-TIME Students Only)

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