Reporting directly to the VP of Operations, this position will dive
deep into data, do analysis, and discover root causes to design
long-term solutions.

Responsibilities:
• Rebuilding the company’s credit decision model in a
more scalable modern format.
• Maintain tune, improve model behavior with data for the
company’s credit decision model for lending operations
to drive profitability.
• Collaborate with business domain subject matter
experts in various departments to understand the
problem and the objectives.
• Building tools to automate data collection.
• Ability to translate complex data into actionable
insights for a non-technical audience
• Research and build innovative predictive statistical
models for all areas of the business.
• Provide mentorship to junior data scientists in aspects of
machine learning data and software engineering and
assist them with practical guidance, when needed.

Qualifications:
• Experience with ML fields, e.g., natural language,
processing computer vision, statistical learning theory.
• 4+ years of industry experience in predictive modeling
data science, and analysis.
• Experience in an ML engineer or date scientist role
building and deploying ML models or hands on
experience developing deep learning models.
• Expertise building modelling systems using one of more
of the following technologies: Python, R.
• Experience in diving into data to discover hidden
patterns, using data visualization tools, writing SQL, and
working with modern tools to develop models.
• Experience writing and speaking about technical
concepts to business, technical, and lay audiences and
giving data-driven presentations.

Education:
• Master’s or Bachelor’s in Quantitative Finance, Statistics,
Computer Science, or Industrial Engineering preferred,
or 5 years of experience in a data science capacity.

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