WorldQuant’s success 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. Great ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess a mindset of continuous improvement. That’s a key ingredient in remaining a leader in any industry.
Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate exceptional talent. There is no roadmap to future success, so we need people who can help us create it. Our collective intelligence will drive us there.
The Role: This is a highly unique opportunity for a Data Scientist to join a new and rapidly growing team. In this role, you will partner with our close-knit team of quantitative researchers, data engineers, technologists, and data sourcing colleagues to analyze and enrich a broad range of structured and unstructured big data.
- Enriching a wide range of large structured and unstructured data into datasets for quantitative analysis
- Enhancing data quality & integrity via a process-orientated approach; developing validation tools to measure the effectiveness of data enrichment; taking full ownership of end-to-end data workflows
- Becoming a domain expert on different fundamental datasets, analyzing & understanding the underlying dynamics and behaviors within the data
- Communicating data-driven analysis and insights to the team
- Developing utility tools that can further automate the software development, testing, and deployment workflow, that facilitate the team’s research efforts
- Using your expertise to provide technical support for global researchers, including diagnosing root causes of technical problems and proposing solutions to developers
What You’ll Bring:
- At least 2 years of experience as a data scientist
- Strong academic background – a minimum of a bachelor’s degree in a technical or quantitative field
- Proven experience of extracting insights from large and complex datasets using SQL and Python (Dask or Spark is a big plus)
- Excellent communication and visual communication skills using Jupyter Notebooks and Plotly, Bokeh or D3
- Expertise in time series analysis and models
- Confidence with Python and prior experience or the ability and willingness to learn C++
- Experience of taking your ideas from Jupyter Notebook to production (working knowledge of Docker and Kubernetes is a big plus)
- Experience in finance or investing related background preferred