Data Scientist, Financial Data Pipelines & Analytics

Point72; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Cubist’s Data Services (CDS) group at Point72 seeks a Data Scientist to join our data team, delivering robust datasets for predictive modelling in finance and enabling billions of dollars in live production trading across global markets. You will onboard new datasets, build data pipelines, reshape and enrich data, and collaborate with investment teams to meet data requirements.

Strong Python/SQL skills and experience with AWS/Linux/Airflow are preferred, with a rigorous quantitative mindset

Qualifications

• Masters in quantitative field required.
• Proficient in Python and SQL.
• Experience with AWS, Linux and Airflow preferred.
• Financial industry experience is a plus.
• Strong communication and interpersonal skills.
• Attention to detail and process discipline.
• Strong oral and written communication.
• Ability to multitask and manage queries.
• Commitment to high ethical standards.

Responsibilities

• Onboarding novel datasets from a huge variety of sources into our platform
• Develop, test and deploy data pipelines, applications and services
• Re-shaping, aggregating, enhancing and creating features from datasets
• Engaging with vendors and internal stakeholders to understand characteristics of datasets
• Defining and automating qualitative data alerts and reports
• Partnering closely with investment teams to ensure their data requirements are met
• Perform preliminary analysis and research to be shared with investment teams

Skills

Python

SQL

Communication

Multitask

Attention to detail

Ethical standards

Oral and written communication

Education

Master's in quantitative field

Tools

AWS

Linux

Airflow

Job description

Cubist’s Data Services (CDS) group at Point72 seeks a Data Scientist to join our data team, delivering robust datasets for predictive modelling in finance and enabling billions of dollars in live production trading across global markets. You will onboard new datasets, build data pipelines, reshape and enrich data, and collaborate with investment teams to meet data requirements.

Strong Python/SQL skills and experience with AWS/Linux/Airflow are preferred, with a rigorous quantitative mindset