24 hours ago
Remote, United StatesSenior
Base Salary
$80k - $150k/yr
Responsibilities
- Design, train, evaluate, and tune document extraction and classification models for structured, semi-structured, and handwritten documents.
- Develop Python components for document preprocessing, data processing, automation, model integration, and reusable solutions.
- Build cloud-native batch and event-driven data pipelines with object storage, analytical databases, workflow orchestration, retries, monitoring, and operational support.
- Implement entity extraction, confidence scoring, quality metrics, page-level validation, exception detection, reconciliation, and human-in-the-loop review workflows.
- Apply OCR, rules-based logic, machine learning, and generative AI appropriately to document-understanding and unstructured-content use cases.
- Implement secure processing controls including encryption, decryption, sensitive-data protections, auditability, and traceability.
- Integrate APIs and systems to ingest documents, publish results, and support downstream workflows.
- Translate document-review procedures into configurable validation rules and technical requirements in collaboration with business subject-matter experts.
- Document model behavior, processing logic, decision outcomes, and operational procedures for technical and non-technical stakeholders.
- Develop scalable, reusable document-processing solutions rather than one-off automations.
Requirements
- Bachelor's degree in Information Systems, Computer Science, Data Analytics, or a related technical field.
- Hands-on experience delivering document-processing or information-extraction solutions in a regulated industry.
- Experience working with sensitive or confidential information and enterprise security controls.
- Familiarity with cloud-based machine learning and data platforms.
- Knowledge of financial-services, legal, healthcare, insurance, or other document-intensive workflows.
- Experience designing exception-based workflows that reduce manual review while preserving quality and control.
- Understanding of supervised model training, labeling strategies, evaluation datasets, confidence thresholds, error analysis, responsible AI, explainability, and review escalation.
- Experience with production data pipelines, data modeling, API and system integration, automated testing, environment promotion, observability, and troubleshooting.
- Ability to communicate complex AI and data-processing concepts to technical and non-technical stakeholders.
Benefits
- Base salary range is $80,000.00-$150,000.00 annually, with potential eligibility for incentive compensation; compensation figures are excluded from the benefit summary.
- Benefits are available according to the employer's benefits program.
- The role is listed for those who work at home in Georgia and includes flexible mobile-work options where the role can be performed effectively, while the company prioritizes in-office presence.
Categories
Data EngineeringML Engineering
About KeyBank
KeyBank, the primary banking subsidiary of KeyCorp (NYSE: KEY), provides retail and commercial banking, payments, wealth management, and equipment financing to consumers and businesses across the United States. Headquartered in Cleveland, it operates a branch-based and digital model, earning interest and fee income from deposits, lending, treasury services, and investment products. KeyCorp was formed in 1994 through the merger of Society Corp. and KeyCorp, creating one of the country’s largest regional banks.