Senior Data Scientist, Operations - AI/ML for FinTech

Archer Daniels Midland; Honolulu (HI); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Flexible time off

Comprehensive health coverage

Paid parental leave

Udemy access

Childcare assistance

Pet insurance discounts

Legal assistance

Job summary

Prosper is seeking a Senior Data Scientist to lead AI/ML initiatives in Operations. You will source, manage, and analyze large data sets, then communicate results to stakeholders to drive decisions.

The role requires collaboration across data science, engineering, and analytics teams while also mentoring a growing team. The candidate will apply GenAI, NLP, ANN and other modeling techniques to improve collections, customer servicing and sales analytics, with a focus on operational efficiency and

Qualifications

• Bachelor’s degree in a quantitative field; advanced degree a plus.
• 7+ years of Data Science, fintech/finance experience preferred.
• Hands-on modeling with Python and SQL; capable of complex analytics.
• Experience with GenAI, NLP, ANN and other modeling techniques.

Responsibilities

• Design and develop AI/ML solutions in Operations.
• Spearhead automation and workflow optimization for efficiency.
• Ensure end-to-end solutions meet technical and business needs.
• Develop data-driven insights and test plans with clear metrics.
• Collaborate across Legal, Risk, Ops, Product and Engineering.

Skills

Python

SQL

GenAI/ML

Data analysis

Communication

Education

Bachelor's degree in Mathematics/Statistics/CS/Engineering/Finance/Economics/Physical Sciences

Tools

BigQuery

BQML

Looker

DBT

GitHub

Bitbucket

Job description

Prosper is seeking a Senior Data Scientist to lead AI/ML initiatives in Operations. You will source, manage, and analyze large data sets, then communicate results to stakeholders to drive decisions.

The role requires collaboration across data science, engineering, and analytics teams while also mentoring a growing team. The candidate will apply GenAI, NLP, ANN and other modeling techniques to improve collections, customer servicing and sales analytics, with a focus on operational efficiency and