Responsibilities:

• Develop key data pipelines from loan purchasing channels to Azure Data Lake

• Establish and grow data warehouses in Snowflake

• Place AI/ML solutions in production using a variety of execution methodologies

• Collaborate with expert data scientists to develop low latency models and ETL processes

• Develop long-term data architecture strategy

• Incorporate new enterprise tools to enhance data and model monitoring

• Establish data quality checks and best practices

Required Qualifications:

• Bachelor s degree in computer science, information technology, engineering or equivalent

• Expert knowledge of Python 2.7 and 3.x (preferred 3.7#43;)

• Experience with Python frameworks such as FastAPI, Starlette, Pydantic

• Expert knowledge of JavaScript and/or TypeScript

• Experience with NodeJS runtime (and optionally ReactJS framework)

• Experience with model productionalization and data processing

• Experience with Azure Data Factory or similar cloud storage infrastructure (GC, AWS, etc.)

• Experience with Powershell and Bash Scripting

• Experience with Snowflake and SQL (SQL ANSI standard)

• Experience with linux distribution (preferably Redhat/RHEL OS)

• Experience with git

Preferred Qualifications:

• Master s degree or higher computer/data science, stats, engineering, or equivalent

• Experience productionalizing Scikit-Learn, XGBoost, and enterprise AI models

• Experience with asynchronous processing and multithreading (preferably AsyncIO)

• Experience with Azure Databricks or similar cloud compute infrastructure (GC, AWS, etc.)

• Experience with Python packages such as Pandas, Numpy, PySpark

• Experience working in the agile framework with tools such as JIRA and Confluence

• Experience building ML algorithms (tree-based, neural networks)

• Experience with financial services and cashflow modeling

• Experience implementing MLOps concept/frameworks

• Experience with ASGI servers

• Experience with Azure DevOps and StreamSets