Description

Our client is seeking a Data Scientist/Analyst to join their data team which delivers efficient data solutions that enable researchers and traders to make informed decisions in real time. This role is central to building and maintaining the infrastructure that powers our trading and research operations. You will work at the intersection of technology and finance, collaborating closely with quantitative researchers, traders, and other technologists to design and implement data models, pipelines, and frameworks that drive business performance.

If you thrive in a collaborative setting and have a strong technical foundation in Python, SQL, and modern data engineering tools, this is an excellent opportunity to make a significant impact.

Responsibilities

~Engage with researchers and traders to identify pain points and opportunities for improvement.

~Gain a comprehensive understanding of the data requirements of investment research teams.

~Translate business needs into technical specifications and actionable solutions.

~Design, develop, and maintain Python-based data applications, frameworks, and services.

~Implement efficient data models and pipelines that support large-scale data processing.

~Optimize existing workflows for performance, scalability, and maintainability.

~Participate in cross-functional projects that require coordination between multiple stakeholders.

~Provide technical guidance and mentorship to junior team members when necessary.

Qualifications

• Bachelor's degree in a technology-related field (Computer Science, Engineering, or similar).
• Strong programming skills in Python, including experience with NumPy and Pandas.
• Significant experience with SQL and relational database design.
• Familiarity with data pipeline orchestration tools such as Apache Airflow.
• Strong design, debugging, and problem-solving skills.
• Excellent analytical and strategic thinking abilities.
• Strong communication skills for interacting with technical and non-technical stakeholders.

Strong value-adds

• Experience in financial services, particularly in trading or research environments.
• Knowledge of event-driven architectures and real-time data processing.
• Familiarity with cloud platforms such as AWS or GCP.
• Understanding of version control systems (e.g., Git) and CI/CD pipelines.