Finance Data Science Advisor - Onsite in DC

Secretaria de Serviços Prefeitura de São Paulo; Washington (District of Columbia); On-site; USD 130,000 - 180,000; Full time

Job summary

Unknown is seeking a senior data science professional to support the Multifamily CECL and DFAST forecasting within the Finance organization. The role emphasizes advanced analytics, econometric methods, and data visualization to drive risk measurement and decision-making.

The candidate will collaborate with data engineers and platform teams, build predictive capabilities, and communicate complex results to non-technical partners through visuals and documentation.

Qualifications

• 6 years of experience in data science, analytics or related finance roles.
• Experience with CECL/DFAST or stress testing knowledge is a plus.
• Strong ability to communicate complex analytics to non-technical partners.

Responsibilities

• Apply statistical modeling, econometrics, and data visualization to finance processes.
• Develop predictive analytics to support risk measurement and financial valuation.
• Coordinate with product and data engineers to align business needs with data capabilities.
• Create and maintain documentation and presentations for stakeholders.
• Oversee development of modeling applications and ensure reliability.
• Present data insights and results to business partners clearly.
• Mentor junior analysts and manage project timelines.

Skills

R programming

Tableau

Python

SQL

DBeaver SQL client software

BitBucket

Education

Bachelor degree or equivalent

Master degree or equivalent in Data Science, Applied Economics, Statistics, or related field

Tools

R programming

Tableau

Python

SQL

DBeaver SQL client software

BitBucket

Job description

Unknown is seeking a senior data science professional to support the Multifamily CECL and DFAST forecasting within the Finance organization. The role emphasizes advanced analytics, econometric methods, and data visualization to drive risk measurement and decision-making.

The candidate will collaborate with data engineers and platform teams, build predictive capabilities, and communicate complex results to non-technical partners through visuals and documentation.