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Klar

Data & AI Scientist – Fraud

Klar

. Design and propose fraud models and rules end to end, including problem framing, feature building, model training and validation, threshold setting, and performance monitoring .

Posted 11/11/2026full-timeMexico City • MexicoJuniorMid-LevelWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in designing and implementing fraud detection models, utilizing advanced statistical methods and machine learning techniques. Proficient in automating workflows with AI agents and communicating complex findings clearly in both Spanish and English.

Highest-signal resume keywords
Advanced PythonSQL Data ProcessingMachine Learning Model TrainingA/B Testing and Experiment DesignLLM-Based Agents

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Fraud Model DesignFeature BuildingStatistical AnalysisLogistic RegressionRandom ForestsGradient BoostingIsolation ForestClusteringGraph AnalysisAnomaly Detection
Soft Skills
Analytical ThinkingClear Communication
Tools & Technologies
AI Coding AgentsGitREST APIsDbtAWSData Orchestrators
Industry Keywords
Data ScienceAutomationFinancial ServicesFraud DetectionQuantitative Analysis

Tech Stack

Tools & technologies
AirflowAWSPythonSQL

About the role

Key responsibilities & impact
  • Design and propose fraud models and rules end to end, including problem framing, feature building, model training and validation, threshold setting, and performance monitoring
  • Detect and size new fraud patterns before they scale and communicate their impact clearly
  • Measure changes with statistical rigor and understand effects on fraud risk and customer experience
  • Build LLM pipelines that turn unstructured text and documents into validated information for models and monitoring
  • Automate workflows with AI agents, including validation, monitoring, prompt engineering, RAG systems, and A/B experimentation
  • Join Klar's Fraud team to help customers use Klar's financial services reliably and securely

Requirements

What you’ll need
  • Bachelor's degree in a quantitative field (Data Science, Mathematics, Actuarial Science, Physics, Engineering, Economics, or related fields)
  • At least 2 years of hands-on experience in data science, automation, AI, operations, or related fields
  • Advanced Python and SQL for data processing
  • Experience training ML models, including logistic regression, random forests, gradient boosting (XGBoost, LightGBM, or CatBoost), Isolation Forest, and clustering
  • Applied statistics for experiment design and A/B testing, hypothesis testing, confidence intervals, and resampling techniques
  • Hands-on experience with LLM-based agents, including structured outputs, function calling, and agentic loops
  • Use of AI coding agents such as Claude Code, Cursor, Codex, or similar
  • Use of development tools such as Git and linters
  • Use of REST APIs
  • Clear written communication in Spanish and English, including for non-technical audiences
  • Analytical thinking to identify patterns and turn observations into recommendations
  • Graph analysis or anomaly detection experience (nice to have)
  • Experience with dbt, a data orchestrator such as Airflow, Dagster, Mage, or similar, and AWS (nice to have)
  • Experience building tools for AI agents, such as MCP servers and skills (nice to have)

Benefits

Comp & perks
  • Competitive salary based on performance and experience
  • Chance of earning Klar stock options
  • 15 days of paid vacation per year
  • Extended maternity and paternity leaves
  • Vacation premium
  • 30 days of Christmas bonus
  • Food vouchers
  • Medical Insurance
  • Computer device
  • Wellhub subscription to offer mental and physical health
  • Sponsored coaching and therapy sessions via a Mental Health Platform
  • A modern centrally located office in Mexico City with free drinks, snacks, and regular social events
  • International work environment with amazing and highly skilled people
  • A world class team that helps you evolve your skills in areas you're interested in
  • Welcoming and inclusive environment