puestos de Machine Learning en United States

Role and Responsibilities

• Lead and conduct quant research activities in areas such as factor modeling, security selection, portfolio risk and construction, transaction cost modeling and attribution
• Gain a good understanding of the discretionary equity investment process and develop suitable quantitative analytics and inputs to augment the process and improve outcomes, in collaboration with the discretionary equity team
• Productionise and integrate quantitative analytics and tools into the investment process and workflow
• Provide quantitative research and analysis support to the discretionary equity investment team
• Champion the use and adoption of quantitative analytics and tools in the discretionary equity investment process
• Develop dashboards and visualisations relevant to support the equity investment process
• Contribute to client marketing efforts as and when required
• Recruit, manage and mentor junior team members as and when required
• Participate in the development of high quality data infrastructure and reporting capabilities including shared code libraries
• Actively lead and participate in regular quant team meetings
• Participate in regular discretionary equity team meetings when appropriate
• Lead and/or participate in adhoc projects as and when required

Requirements

• Eight or more years relevant industry experience in quantitative equity investment research and portfolio management (additional experience in other assets classes a plus)
• Master’s or PhD degree in quantitative field such as engineering, physics, applied mathematics, statistics etc
• CFA is a plus
• Passion and enthusiasm for quantitative research and investment management
• Good general understanding of global financial markets and specific equity asset class expertise
• Experience working with dynamic discretionary equity strategies and investment processes (long-short and absolute return strategies an advantage)
• Good understanding and practical application of equity factor risk models (eg. Barra, Axioma)
• Good understanding and practical application of portfolio risk analysis and risk and return attribution
• Experience with market, industry, style, company and equity security analysis
• Strong programming ability in Python and SQL
• Experience creating and using data visualisation tools (eg. PowerBI, Tableau)
• Experience with version control systems and DevOps tools (eg. Git, Bitbucket)
• Experience with workflow management tools (eg. Prefect, Airflow)
• Knowledge and application of machine learning and LLMs a plus
• Fluent in spoken and written English and Chinese. We need a good command in Chinese language to correspond with our HQ in both Hong Kong and Shanghai.

Attributes

• Collaborative and enjoys working in a team but also able to work well independently
• Entrepreneurial and energetic self-starter
• Well-organised with good attention to detail
• Articulate, good written communication ability and good interpersonal skills
• Broad-minded and open to debate and challenge
• Intellectually curious and innovative
• Diligent with strong sense of responsibility
• Good project and time management ability