Predictive Data Engineer: Python for Sports Trading

Susquehanna International Group, LLP; Bala Cynwyd (PA); On-site; USD 140,000 - 230,000; Full time

Benefits offered by this job

Excellent salary and benefits

Attend world sporting events

Job summary

Susquehanna International Group, LLP in Bala Cynwyd, PA is seeking an experienced Quantitative Data Engineer for the Prediction Markets team to design, implement, and maintain our next‑gen analysis and trading platform.

You will collaborate with Quantitative Researchers and other developers to source and cleanse data, build data pipelines, research trading opportunities, and deploy interactive reports that influence trading strategies.

Qualifications

• Experience with numeric data storage methodologies.
• Experience with processing of large and varied data sets.
• Ability to understand mathematical algorithms and develop high-performance implementations.
• Interpersonal and communication skills to interact with traders, quantitative analysts, and other software developers.

Responsibilities

• Source and cleanse data, develop and maintain data pipelines for quant research and trading.
• Assist with researching new trading opportunities.
• Develop, maintain and deploy interactive and packaged reports that influence trading strategies.
• Performance-tune existing applications and data flows for efficient processing of large data sets.

Skills

Python

NumPy

pandas

Agile methodologies

Cloud Computing

Kafka

Kubernetes

Education

PhD/MS/BS in Computer Science or related STEM field

Tools

Kafka

Kubernetes

Cloud Computing

Job description

Susquehanna International Group, LLP in Bala Cynwyd, PA is seeking an experienced Quantitative Data Engineer for the Prediction Markets team to design, implement, and maintain our next‑gen analysis and trading platform.

You will collaborate with Quantitative Researchers and other developers to source and cleanse data, build data pipelines, research trading opportunities, and deploy interactive reports that influence trading strategies.