Build efficient data pipelines for financial data flows whilst ensuring data and analytics are leveraged for future growth.
Monitor data movement, transformation logic and performance of all pipelines as required to maintain data integrity and quality supplied to ML processes.
Designing and implementing data solutions for new data and servicing initiatives and providing continuous oversight for existing solutions to maintain data accuracy, service quality and solution performance.

Requirements

Undergraduate (junior/senior preferred) or graduate students in Computer Science, Data Science, or a related field.
Experience designing, building, and maintaining data pipelines for large-scale data solutions.
Proficiency in Python, pandas and data science libraries plus solid SQL skills for querying and manipulating large datasets. Experience with PostgreSQL is preferred.
Ability to design scalable, secure data models and implement best practices for data storage and retrieval.
Familiarity with AI for coding, machine learning applications and approaches to maintain high-quality, compliant data for AI-driven use cases. Experience with data unit testing is preferred.
Good communication skills to collaborate with cross-functional teams - including data scientists, AI engineers, and business stakeholders - to deliver secure, high-performing data solutions.
Experience with unstructured data processing is a plus.
Experience with Azure cloud services is a plus.

Benefits

Compensation: $20-30 per hour
Hybrid working: three days per week in our Manhattan office.
An opportunity to work at the forefront of AI-driven finance, tackling genuinely complex and high-impact challenges.
Hands-on exposure to advanced ML, LLM, and data technologies within real production systems.
A collaborative, high-ownership start-up environment offering exceptional learning opportunities.
The chance to help shape the future of Family Office and Asset Management technology.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data pipelinesPythonpandasSQLPostgreSQLdata modelingdata storagedata retrievalmachine learningdata unit testing

Soft Skills

communicationcollaboration