Forward-Deployed Architect, Credit Analytics – ML Platforms

This is a fully remote position, open to applicants in Poland.

📋 Description

• Convert business challenges into architectural frameworks, implementation plans, and acceptance criteria.

• Develop the trajectory from functional models and dashboards to a fully operational ML platform.

• Create reproducible workflows for data preparation, feature engineering, training, validation, scoring, and deployment.

• Establish version control for code, data, models, and calibration logic.

• Collaborate on assessments of default probabilities, prepayment, lifetime risk, and loss estimates.

• Enhance data foundations through traceability, investigation of data quality, documentation, and automated checks.

• Increase the reliability of the Snowflake-backed analytics application, focusing on deployment, testing, permissions, and model-output integration.

• Adopt MLOps practices, including releases, monitoring, failure management, rollback, and operational documentation.

• Design with privacy, access control, audit capability, and model governance in mind.

• Facilitate technical discussions, review code, assist engineers, and keep clients informed.

• Evaluate opportunities for utilizing natural language or LLM-assisted analytics.

⛳️ Requirements

• Proven experience in designing and delivering production-level data or ML systems, with responsibilities extending beyond prototypes and architectural diagrams.

• Proficient in Python and SQL with strong practical skills.

• Hands-on MLOps experience, including the creation of reproducible pipelines, model and data versioning, testing, deployment, and monitoring.

• Familiarity with cloud data platforms and modern data warehouses; experience with Snowflake is especially relevant.

• Knowledge of model evaluation, calibration, data leakage, population changes, model quality, and system reliability.

• Capability to navigate incomplete documentation and ambiguous business definitions.

• Strong client-facing communication skills in English.

• Experience leading a small technical team while remaining actively engaged in implementation tasks.

• Additional beneficial experience: credit-risk, lending or servicing analytics; regulated financial services delivery and model governance; Streamlit, Azure ML, semantic data layers, or Snowflake analytics applications; configurable ML products; natural-language analytics, text-to-SQL, or LLM-assisted workflows.

🏝️ Benefits

• Opportunities for professional growth and development.

• Collaborative and innovative work environment.

• Competitive salary and benefits package.