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Tardis Group · Singapore, Singapore

Data Scientist

mid_levelfull timePosted 6 days ago
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Stack mentioned

data-sciencedata-structuresetlmicroservicesdata-governanceanomaly-detectiondata-analysisstatisticspythonsqllinuxawsapache-airflow

As a Data Scientist, you will be instrumental in supporting a high-throughput quantitative research platform and ensuring the seamless execution of live trading algorithms across diverse global asset classes, including equities, futures, and options.

Responsibilities

- Design, build, test, and maintain robust ETL/ELT pipelines, microservices, and workflows for automated dataset ingestion.

- Clean, structure, aggregate, and engineer actionable signals/features from diverse financial and alternative datasets.

- Partner closely with quantitative research teams and external vendors to analyze dataset characteristics and address specialized data needs.

- Establish automated data quality frameworks, anomaly detection, and qualitative reporting mechanisms.

- Conduct preliminary data analysis and exploratory research to support new strategy development and quantitative workflows.

Qualifications

- Master’s degree preferred in Financial Engineering, Computer Science, Statistics, or a related quantitative/analytical field.

- Strong proficiency in Python and SQL for data manipulation and system building.

- Familiarity with Linux environments, modern cloud platforms (e.g., AWS), and workflow orchestration tools (e.g., Airflow) is a strong plus.

- Exposure to financial markets or quantitative investment data is preferred but not required.

- Excellent problem-solving skills with meticulous attention to detail and process execution.

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