Machine Learning Scientist

• Design, develop, and evaluate machine learning models for fraud detection, including fraud scoring and ensemble models that combine multiple sources of evidence
• Analyze large-scale datasets to identify complex patterns, relationships, behaviors, and anomalies, developing new signals to improve fraud detection
• Define robust experimentation and evaluation methodologies, including model calibration, operating thresholds, and performance metrics under realistic production conditions
• Develop interpretable and explainable ML approaches that help internal stakeholders and customers understand fraud scores and decisions
• Explore innovative approaches to fraud decisioning, including human-in-the-loop techniques and causal methods
• Collaborate with Product and Fraud Domain Experts to translate real-world fraud challenges and production feedback into effective machine learning capabilities
• Partner with Data Engineering to transform ML prototypes into scalable, maintainable, production-ready solutions
• Contribute to model monitoring, governance, technical documentation, ML tooling, and shared best practices across the team
• Build machine learning solutions that improve fraud detection and explainability across Mitek's digital identity products
• Deliver measurable business value through improved fraud decisions and scalable production capabilities

• A Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, Machine Learning, or a related quantitative field, or equivalent practical experience
• Approximately 5 years of experience as a Data Scientist, Applied ML Scientist, or in a comparable role
• Strong knowledge of statistical methods, supervised machine learning, and model evaluation, particularly for highly imbalanced classification problems
• Hands-on experience in feature engineering and machine learning model development using complex behavioral, relational, or contextual data
• Strong programming and analytical skills using Python, PySpark, and SQL
• Experience working with cloud-based machine learning and data infrastructure
• Strong spoken and written English skills
• Comfortable collaborating with distributed teams across different offices and time zones
• Experience in fraud detection, financial crime, payments, digital identity, risk, or Trust & Safety
• Knowledge of advanced machine learning approaches such as graph-based methods, representation learning, or causal AI
• Experience with modern data lakehouse or real-time data technologies such as Apache Iceberg or Apache Pinot
• Experience taking machine learning solutions from experimentation into scalable production environments
• Confidence working in Linux environment

• Wellness: Universal, supplemental, and private healthcare plan choices based on country specifics
• Retirement/pension plan contributions
• MTK stock plan participation
• Life event & disability coverage
• Generous annual leave
• Company holidays
• Volunteer time off
• E-learning license
• Tuition reimbursement
• Hackathons
• Home office setup allowance
• Pet insurance
• Identity theft protection
• Legal assistance
• Base + 10% Annual Bonus + Equity