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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying AI and machine learning solutions, with a strong focus on the end-to-end data science lifecycle and advanced analytics in financial services. Proficient in developing scalable AI/ML pipelines and mentoring teams while ensuring data integrity and responsible AI practices.
Highest-signal resume keywords
AI Solution DevelopmentGenerative AI SolutionsProduction-Grade AI/ML SolutionsPython ProgrammingFinancial Services Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningStatistical ModelingFeature EngineeringModel ValidationAnomaly DetectionOptimizationExperimentationData Science LifecyclePrompt Engineering
Soft Skills
MentoringCollaborationCommunication
Tools & Technologies
AzureAWSDatabricksSnowflakePyTorchScikit-learnXGBoostSpark
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree in Artificial IntelligenceMaster's Degree in Data Science
Industry Keywords
FintechPaymentsBankingFinancial ServicesHigh-Volume Transactional Data
Tech Stack
Tools & technologiesAWSAzurePythonPyTorchScikit-LearnSparkSQL
About the role
Key responsibilities & impact- Design, develop, and deploy AI and machine learning solutions for complex business problems across payments and financial services
- Own the end-to-end data science lifecycle, including problem formulation, exploratory analysis, feature engineering, experimentation, model development, validation, deployment, monitoring, and continuous improvement
- Apply advanced analytics and AI to merchant and consumer intelligence, fraud and risk, personalization, forecasting, anomaly detection, and authorization optimization
- Partner with product, engineering, architecture, and business teams
- Mentor data scientists and translate emerging AI research into reusable, production-ready capabilities
- Develop scalable AI/ML pipelines and production solutions with testing, observability, governance, and performance optimization
- Create training, evaluation, and synthetic datasets while maintaining data integrity, privacy, security, and responsible AI practices
- Develop and adapt domain-specific models through prompt and context engineering, retrieval, fine-tuning, model optimization, and rigorous evaluation
- Build generative and agentic AI solutions, including foundation-model applications, retrieval-augmented generation, tool-calling workflows, structured outputs, and multi-agent systems
Requirements
What you’ll need- 5+ years of experience delivering high-impact AI solutions
- 2+ years of hands-on experience developing LLM and generative AI solutions, including autonomous agents, foundation-model architectures, and production-grade RAG pipelines
- Experience building production-grade AI/ML solutions using Azure, AWS, Databricks, Snowflake, or comparable technologies
- Strong programming skills in Python and SQL
- Experience with PyTorch, scikit-learn, XGBoost, and Spark
- Deep applied AI expertise across machine learning, deep learning, statistical modeling, experimentation, forecasting, anomaly detection, optimization, and model validation
- Strong fintech, payments, banking, or financial-services experience
- Practical knowledge of high-volume transactional data and financial-data controls
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or another quantitative field from a recognized institution
- Valid and unrestricted U.S. work authorization required
- Temporary visas including F-1 (OPT, CPT, STEM), H-1B, H-2, and TN are not accepted; candidates requiring sponsorship now or in the future will not be considered
Benefits
Comp & perks- Annual incentive opportunity, potentially delivered as a mix of cash bonus and equity awards
- Approximately 10% travel off-site or to other office locations
