AI Data Analyst - Merchant Acquisition
New
P
PaynadaMerchant services, payments
United StatesFull-Time
SalaryExpected pay range is $70-80,000 per year. This position is full time and eligible for full benefits package as well.
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Job Details
- Required Skills
- PythonSQLLLM
Requirements
- Have advanced training or equivalent professional experience in data science, applied statistics, machine learning, computer science, econometrics, quantitative marketing, or a closely related field.
- Demonstrate experience with predictive modeling, propensity modeling, lead scoring, customer analytics, or another classification or ranking problem.
- Have strong Python and SQL capabilities.
- Have experience with unstructured text, call transcripts, conversation analytics, or natural-language processing.
- Be familiar with large language models and their use in structured information extraction, classification, and research workflows.
- Be able to develop disciplined data-collection and validation plans when historical data is limited.
- Understand experimental design, prospective validation, model evaluation, data leakage, overfitting, and selection bias.
- Be able to combine qualitative business research with quantitative analysis.
- Demonstrate product judgment and interest in building a commercial platform.
- Be able to work independently, define priorities, and communicate directly with company leadership.
- Handle recorded conversations and merchant information confidentially and responsibly.
- Preferred: experience in merchant acquiring, credit-card processing, payments, fintech, banking, financial services, B2B sales-call analysis, or sales-intelligence systems.
- Preferred: familiarity with merchant categories, processing statements, pricing structures, interchange, chargebacks, point-of-sale systems, and processor switching.
- Preferred: experience with speech-to-text systems, embeddings, retrieval systems, LLM evaluation, external business data, or data-product deployment and monitoring.
Responsibilities
- Develop the research, data, and AI strategy for a merchant lead-intelligence platform.
- Analyze recorded sales conversations using transcription, NLP, LLMs, and human-reviewed research.
- Create frameworks and quality-control procedures for extracting and labeling information from calls.
- Identify signals that predict sales progression and develop an initial rules-based lead-scoring model.
- Develop statistical and machine-learning models as prospective outcome data becomes available.
- Evaluate external business data sources and connect relevant signals to prospect identification.
- Design controlled experiments comparing AI-selected leads with the existing lead-selection process.
- Build or manage an initial prototype and subsequent production platform, and integrate recommendations into sales workflows.
- Establish performance metrics, documentation, data-governance practices, and safeguards for sensitive information.
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