Senior AI Reporting Engineer

Razer Inc.

full-time

Posted on: 9/24/2025

Origin: • 🇨🇳 China

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Senior

AirflowAWSAzureCloudETLGoogle Cloud PlatformHadoopPythonPyTorchScikit-LearnSparkSQLTableauTensorflow

About the role

Perform data-driven risk assessments and compliance monitoring; analyze complex datasets to identify patterns, anomalies, and emerging risks impacting regulatory and internal compliance.
Design, develop, and maintain automated financial reports and dashboards, applying AI-driven methods to streamline data processing and reporting.
Leverage LLMs and AI tools for intelligent data validation, anomaly detection, reconciliation, and report generation.
Collaborate with finance, payment operations, and engineering teams to gather requirements and implement AI-enabled reporting solutions.
Enhance ETL processes with automation and machine learning techniques to improve financial data quality and reduce manual intervention.
Develop reusable AI/ML components for financial reporting tasks such as fraud detection signals, transaction pattern analysis, and reconciliation workflows.
Integrate financial reporting systems with generative AI tools (e.g., ChatGPT, LangChain) for query handling, report explanation, and natural language summaries.
Partner with data engineers to ensure robust financial data models, pipelines, and compliance with internal and regulatory standards.
Perform advanced troubleshooting, leveraging AI-assisted diagnostics to identify and resolve discrepancies in settlement and merchant data pipelines.
Stay up to date with AI and big data technologies, evaluating opportunities to bring innovation into financial reporting workflows.

Bachelor's or Master's degree in Computer Science, Data Engineering, Finance, or a related field.
4+ years of experience in data engineering or reporting, with exposure to financial reporting and transaction data preferred.
Strong skills in SQL and Python.
Experience in ETL orchestration tools (Airflow, dbt, Talend, or similar).
Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Familiarity with LLMs and generative AI tools.
Experience integrating AI into financial or reporting workflows (e.g., anomaly detection, NLP-driven reporting).
Proficiency with data visualization tools (Tableau, Power BI, QuickSight).
Familiarity with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Presto, or Hadoop).
Solid understanding of financial transaction data, reconciliation processes, and settlement workflows.
Strong problem-solving, documentation, and communication skills.
Nice to have: experience applying prompt engineering and embeddings for financial data analysis.
Nice to have: Knowledge of MLOps practices for deploying and monitoring AI-driven reporting pipelines.
Nice to have: Exposure to fintech, payments, or e-commerce reporting systems.