Finance Data Science Advisor ( SME – Financial and IT Modeling & Analytics)

SES; Washington (District of Columbia); On-site; USD 140,000 - 190,000; Full time

Job summary

SES in Washington, DC, is seeking a Finance Data Science Advisor to apply advanced analytics to CECL and DFAST forecasting. The role blends economics, statistics, and computational methods to support risk measurement and financial valuation.

You will drive modeling and visualization, collaborating with data engineers and stakeholders to deliver actionable insights. The position requires 6+ years of experience and a strong background in ML/NLP, forecasting, and cross-functional leadership.

Qualifications

• 6 years of experience in finance data science or related field.
• Masters degree in Data Science, Applied Economics, Statistics, or related field.
• Familiarity with ML and NLP techniques.
• Forecasting and stress testing knowledge (DFAST).
• Strong ability to manage technical analysis and lead a team.

Responsibilities

• Use advanced tools to create algorithms for CECL and DFAST forecasting.
• Research and evaluate model results; perform credit analyses for adverse scenarios.
• Coordinate with product, data engineers, and platform teams to align business needs.
• Apply statistical modeling across CS, econometrics, data visualization disciplines.
• Build predictive analytics within the team and integrate data with models.
• Innovate through industry practices in research, testing, and deployment.
• Oversee design and build of new modeling applications for risk and valuation.
• Communicate complex ideas via visualizations and documentation for non-technical partners.

Skills

R programming

Tableau

Python

SQL

Bitbucket

Education

Bachelor degree or equivalent

Masters degree in Data Science or related

Tools

DBeaver SQL client

Job description

Finance Data Science Advisor ( SME – Financial and IT Modeling & Analytics)

3-5 days per week onsite – Washington, DC

NO C2C or 3rd Party

Top 5 Technical Skills:

1. R programming
2. Tableau
3. Python
4. SQL
5. DBeaver SQL client software
6. BitBucket

Job Description:

The Finance – Data Science – Advisor role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

• Use advanced mathematical, analytical, or econometric tools to create algorithms and analyses that will be used to support the Multifamily CECL and DFAST/forecasting processes within the Finance organization.
• Research and evaluate model results and perform credit-related analyses for both expected and stress scenarios including CECL/DFAST.
• Coordinate team activities with product and/or business owners, data engineers, and platform teams to understand business needs and current capabilities, data availability, and alternative uses to drive success of parts of projects, programs, or products.
• Ensure application of statistical modeling capabilities from disciplines, such as computer science, computational science and methods, statistics, econometrics, data optimization, and data visualization.
• Build predictive analytic capabilities within the team to enhance the delivery of business applications, and support the integration of data and statistical models or algorithms.
• Apply innovative industry practices in research and testing to product development, deployment, and maintenance.
• Oversee the design and build of new modeling applications to support risk measurement, financial valuation, decision making, and business performance for parts of products or initiatives.
• Ensure the team communicates complex ideas and solutions effectively to business partners through data visualizations, technical documentation, and non-technical presentation materials.

Minimum Required Experiences

• 6 years

Desired Experiences

• Bachelor degree or equivalent
• A Masters degree or equivalent in Data Science, Applied Economics, Statistics, or other similar graduate studies
• Familiarity with advanced techniques including machine learning and natural language processing (NLP)
• Prior quantitative and finance training, including forecasting/stress testing (DFAST) knowledge.
• Ability to direct and evaluate the more technical aspects of data analysis and research, while also managing team in a timely manner to focus on the broader context and key impacts of the analysis
• Ability to build and maintain strong business relationships with partners
• Strong written and verbal communication skills
• Relationship management including managing and engaging stakeholders, partners, customers, and building relationship networks
• Strong analytical and problem-solving skills to conduct and manage analysis to address complex business problems
• Programming including coding, debugging, and using relevant languages such as Python, R, SQL, or similar
• Experience in the process of analyzing data to identify trends or relationships to generate business insights and inform conclusions about the data
• Expertise in visualizing data to identify, summarize and explain observed data patterns

Tools

• R programming
• Tableau
• Python
• SQL
• DBeaver SQL client software
• BitBucket