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Spoton

Compliance Systems & Data Analyst

Kraków, Lesser Poland Voivodeship, PolandHybrid · Poland
FullTime · Legal & Compliance
POSTED 28 OCTVERIFIED 45M AGO
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Open for
6d
since 28 Oct
Hiring · 30d
71
0 net · open roles
LLMs

About SpotOn

We’re not just building restaurant tech, we’re giving independent restaurants the tools to compete and win. From our award-winning point-of-sale to AI-powered profit tools, everything we do helps operators boost profit, work smarter, and keep their best people. And every solution is backed by real humans who actually give a sh*t about helping restaurants succeed.

Named the #1 Restaurant POS by G2 (Summer 2026), based on ratings from real users

Rated the top-rated point-of-sale (POS) for restaurants, bars, retail, and small businesses by Capterra users

Awarded Great Places to Work and Built In’s Best Workplaces for multiple years running

We move fast, care hard, and fight for independent restaurant operators to do what they love, and love doing it. If you’re looking to make an impact with heart and hustle, SpotOn is the place for you.

Reporting to the Director of Compliance Systems & Data, the Compliance Systems & Data Analyst leads the design, implementation, and management of technology to streamline and continuously improve our Underwriting and KYC solutions. This role will lead the identification, analysis, and optimization of Know Your Customer/Business (KYC/KYB) and Underwriting workflows by implementing AI, machine learning, and Large Language Models (LLMs) to reduce manual reviews and accurately identify risks. The goal is to develop and integrate technology solutions that align with industry best practice that can both scale AND create operational efficiencies.

This person will focus on "Know Your Customer" (KYC) and Credit Underwriting processes throughout the customer lifecycle with new technologies (like AI, ML, Regex detection, OCR etc) streamlining identity verification, completing ongoing data, AI and model validations, screening (PEP, OFAC), risk assessments, and monitoring while reducing manual errors. This role involves analyzing workflows, supporting AI/ML solutions,validating models and ensuring ethical data and AI use through continuous performance monitoring and testing. Experience with identity solutions & case management systems for fraud and anti-money laundering (AML) is imperative.

On a daily basis, you will

Core Responsibilities: Driving Compliance Automation & Optimization

Process Optimization & Analysis

Analyze existing manual Know Your Customer (KYC) and Anti-Money Laundering (AML) workflows (including data collection, document verification, and watchlist screening) to identify inefficiencies and bottlenecks.

Automate manual processes to increase speed, accuracy, and performance, monitoring Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs) for continuous improvement.

Test AI decision models involving identity to meet EU AI and CA ADMT requirements

Propose process or policy changes, and recommend system and/or vendor implementation updates, as applicable.

Technology Implementation & Solution Development

Develop and implement Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) solutions for critical tasks such as:

Data extraction (using OCR).

Biometric verification and automated decision-making (ADMT).

Regex detection for monitoring and cash flow optimization.

LLM Model development

Contribute to the development of risk scorecards, credit policies, and overall process structure.

Help implement enhancements to identity verification, onboarding automation, customer risk scoring, and OFAC/Sanctions & PEP screening.

Risk Management & Compliance

Ensure automated systems accurately detect, assess, and score risks (including Enhanced Due Diligence - EDD) to maintain regulatory and card scheme standards.

Develop risk scoring models to move toward automated underwriting, incorporating various models and decision tools.

Oversee data and model validation: test and validate decisioning and AI solutions, identifying appropriate data sources, and validating the integrity, accuracy, and quality of data flowing to decisioning and reporting systems.

Ensure ethical AI use, data privacy, and adherence to all governance requirements.

Source · SpotonFirst seen 2 NovOriginal ↗