Financial Data Analyst (Remote)

• Role: Financial Data Analyst (Remote) • Location: Remote (Work from Anywhere) • Job Type: Contract • Payout: $14 - $36/hour Role Overview: We are hiring for one of our clients, seeking a Workflow Annotator — Finance & Data Analysis to work on a contract basis. You will analyze financial and data workflows to identify patterns and anomalies. The role involves structured annotation of datasets for model training and validation. Key Responsibilities: • Annotate financial transaction data to support machine learning model development. • Review and label structured datasets for accuracy and consistency. • Identify discrepancies in financial workflows and document findings. • Collaborate with data scientists to refine annotation guidelines. • Ensure compliance with financial data privacy and security standards. Required Skills & Qualifications: • Experience with financial data analysis or auditing. • Proficiency in data annotation tools or platforms. • Attention to detail for identifying patterns and anomalies. • Ability to follow structured annotation guidelines. • Familiarity with financial terminology and workflows. More About the Opportunity: This role offers a unique opportunity to work with a global leader in the financial services industry, contributing to the improvement of AI-driven financial automation systems. The role is integral to enhancing data quality for predictive modeling in finance. Equal Opportunity Employer: We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications. Apply Now! Show more Show less

Experience with financial data analysis or auditing. Proficiency in data annotation tools or platforms. Familiarity with financial terminology and workflows. Ability to follow structured annotation guidelines. Attention to detail for identifying patterns and anomalies.

Annotate financial transaction data to support machine learning model development. Review and label structured datasets for accuracy and consistency. Identify discrepancies in financial workflows and document findings. Collaborate with data scientists to refine annotation guidelines. Ensure compliance with financial data privacy and security standards.