Abdulsomod D.

Key Skills

Software

Other

Don't disclose

Top Subject Matter

Business Domain Expertise

Financial Compliance & Risk Analysis

and HTML-based tasks

Top Data Types

Text

Image

Document

Top Task Types

Prompt + Response Writing (SFT)

Fine-tuning

Bounding Box

Classification

RLHF

Entity (NER) Classification

Freelancer Overview

Freelance AI Model Trainer / AI Generalist Trainer (Self Employed). Brings 9+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other and Don't disclose. Education includes Bachelor of Science, New York University Stern School of Business (2018). AI-training focus includes data types such as Text and Image and labeling workflows including Prompt + Response Writing (SFT), Fine-tuning, and Evaluation.

Labeling Experience

Freelance AI Model Trainer / AI Generalist Trainer (Self Employed)

OtherTextPrompt + Response Writing (SFT)

Trained AI models for ChatGPT and similar platforms by evaluating and refining business, finance, and HTML-based tasks to ensure responses were accurate and relevant. Performed quality assurance by reviewing large volumes of model outputs, correcting logic, grammar, and structural issues to improve reliability and usefulness. Systematically detected recurring error patterns, optimized prompts, and ranked responses to refine internal quality guidance and improve model performance standards. • Evaluated and refined business/finance/HTML-related task responses • Reviewed 500+ AI-generated responses for logic and quality issues • Detected and reported 50+ recurring finance/business error patterns • Ranked outputs and contributed to guideline development

2023 - Present

Senior Financial Analyst - Global Investment Partners

Image

Reviewed and validated large-scale financial datasets to ensure high accuracy for training and valuation use cases. Created labeled examples of financial statements and investor-ready summaries to serve as reference ground truth for downstream model fine-tuning. Developed structured taxonomies for expense categorization to improve consistency for financial analysis workflows. • Verified dataset quality and accuracy for M&A valuation workflows • Produced variance analyses and labeled financial statement examples • Built and refined expense categorization taxonomies • Performed QA/QC of automated Power BI reporting outputs

2022 - Present

Artificial Intelligence Director, WidgetWorks Inc.

OtherText

Led AI and ML initiatives aimed at creating business solutions and improving operational effectiveness. Collaborated with business units to analyze workflows and identify opportunities where AI could improve processes and outcomes. Designed and executed proofs-of-concept to evaluate GenAI business value while supporting the establishment of a GenAI Center of Excellence. • Analyzed business workflows for AI-driven improvement • Built and ran GenAI proofs-of-concept for value assessment • Supported GenAI Center of Excellence creation • Engaged leadership and communicated AI project outcomes and concepts

2018 - Present

AI Specialist, Quantum Solutions LLC

Don't discloseTextFine-tuning

Provided AI model and analytics work that included governance, risk assessment, and ongoing compliance monitoring to support responsible AI utilization. Collaborated with data scientists to refine project objectives and improve data analysis techniques used for building and operating AI systems. Conducted research to integrate updated AI trends into existing frameworks while supporting ethical and legal evaluation of AI solutions. • Established project objectives and refined data analysis techniques • Optimized AI systems for accuracy and performance • Developed AI governance policies and performed risk assessments • Monitored compliance with AI regulations and best practices

2018 - 2023

Financial Analyst - TechCorp Industries

ImageBounding BoxClassification

Annotated profit and loss line items, budget assumptions, and forecast drivers for multiple business units. Performed comparisons between human and model forecasts and documented edge cases to support retraining. Maintained data integrity across financial databases using consistent labeling rules for revenue and cost data. • Built supervised-learning oriented training inputs from financial statements • Documented discrepancies and edge cases found in forecasts • Enforced consistent revenue and cost labeling rules • Curated and validated data used for forecasting activities

2020 - 2022

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Education

Work History