WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.
WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.
Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.
The Role: This is a highly unique opportunity for a Quantitative Researcher to join a new and rapidly growing team. In this role you will partner with a close-knit team of data scientists, data engineers, technologists and data sourcing colleagues to identify and research new sector or broad Alphas based on a deep understanding of fundamentals.
- Develop a structured and methodical research agenda combining fundamental knowledge, data exploration and quantitative analysis.
- Become a domain expert on each fundamental topic you cover, identify key information drivers to target your research.
- Conduct detailed data exploration to acquire a comprehensive understanding of the data used to generate Alphas; enrich a wide range of structured and unstructured data into datasets to enable your quantitative research.
- Take a process orientated approach to understand the value drivers of your Alphas
What You’ll Bring:
- At least 2 years of relevant financial research experience
- Proven experience of extracting insights from large and complex datasets using SQL and Python. Experience with alternative datasets a plus.
- Demonstrable financial knowledge - passed at least Level I of the CFA program, or similar financial qualification (i.e., MBA or accountancy background). Thorough understanding about various valuation approaches and methods.
- Expertise in time series analysis and models.
- Proficient in coding in C/C++ and Python.
- Excellent communications skills (both written and oral English).
- Strong analytical and conceptual skills encompassing finance and related areas of financial investment.
- Familiarity with various research/database platforms (Bloomberg, Reuters etc.) would be preferred.
직무: 해당 직무는 퀀트 연구원으로써 WorldQuant에서 빠르게 성장하고 있는 신규 프로젝트인 Deep Research에 합류할 수 있는 매우 특별한 기회입니다. 여러분은 데이터 사이언티스트, 데이터 엔지니어및 데이터 소싱 전문가로 구성된 팀과 긴밀히 협력하여 펀더멘탈(기업 재무정보)에 대한 깊은 이해를 바탕으로 섹터 혹은 시장 전체에 대한 알파 개발 및 연구를 담당하게 됩니다.
- 재무 관련 지식, 데이터 탐구 및 정량적 분석을 포함한 체계적인 연구 과제를 개발합니다.
- 담당하는 재무 분야에 대한 도메인 전문가가 되어 해당 연구의 주요 핵심 정보를 분석합니다.
- 알파 개발에 사용되는 데이터에 대한 포괄적인 이해도를 갖추기 위해 데이터를 정밀하게 분석합니다. 다양한 정형 및 비정형 데이터를 연구에 활용할 수 도록 가공합니다.
- 개발한 알파의 핵심 가치를 이해하기 위해 프로세스 중심 접근 방식으로 연구합니다.
자격요건:
- 최소 2년의 관련 금융 연구 / 재무 분석 경력이 있으신 분
- SQL및 Python을 사용해 복잡한 빅 데이터셋에서 인사이트를 도출한 경험이 많으신 분
- 입증된 금융 지식을 갖춘 분 - CFA 레벨 1 을 취득하셨거나 이와 비슷한 금융 자격 요건(예: MBA혹은 회계 경력 등)을 갖추신 분. 다양한 밸류에이션 접근법과 방법론에 대한 이해도가 깊으신 분
- 시계열 분석 및 모델링에 능숙하신 분
- C/C++ 또는 파이썬 프로그래밍에 능숙하신 분
- 영어로 의사소통이 가능하신 분 (서면 및 구두)
- 금융 및 투자 관련 분야에 대한 우수한 분석력을 갖추신 분
- 다양한 연구/데이터베이스 플랫폼 (Bloomberg, Reuters 등) 사용 경험 우대
합격하신 분들은 서울 지사에서 근무하게 될 예정입니다.
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