Macro & Credit Research Economist
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Job Location:
New York City, NY - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
We believe that the way people interact with their finances will drastically improve in the next few years. Were dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo SoFi several of the Fortune 500 and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaids network covers 12000 financial institutions across the US Canada UK and Europe. Founded in 2013 the company is headquartered in San Francisco with offices in New York Washington D.C. London and Amsterdam.
The Macro & Economic Insights team is responsible for translating Plaids unique high-frequency transaction and balance data into rigorous forward-looking insights about household financial health credit dynamics and the broader economic cycle. The team builds internal indicators research outputs and external-facing analysis that leverage Plaids data advantage to inform strategy products and market narratives.
As the Macro and Credit Research Economist you will build and own macroeconomic and credit indicators derived directly from raw transaction data. You will develop forecasting models identify economic turning points and produce rigorous analysis that informs internal decisions and external research.
Responsibilities:
- Work directly with large-scale messy transaction data to build the transformations filters and statistical frameworks needed to extract reliable economic and credit-cycle signals.
- Develop forecasting models that quantify household financial conditions credit dynamics and broader economic trends emphasizing real-world performance and interpretability.
- Identify leading indicators and turning points across liquidity spending patterns credit behavior income stability and other elements of household financial resilience.
- Build methodologies that detect changes in economic regimes and risk conditions based on high-frequency data.
- Produce rigorous backtests scenarios and real-time indicators that inform internal strategic decisions and external-facing research.
- Create investor-grade written analyses dashboards and periodic briefings that synthesize model outputs with clear economic context.
- Benchmark internal measures against official statistics and market expectations highlighting where Plaids data provides differentiated early insight.
- Collaborate with product policy comms and GTM teams to shape how selected findings inform data products strategic narratives and outreach.
Qualifications:
- PhD in Economics (macro finance monetary applied micro) or an equivalent quantitative field.
- 4-8 years of applied experience in macro strategy credit investing systematic research or consumer credit analytics.
- Strong econometric and time-series modeling skills with experience linking micro data to macro outcomes.
- Proficiency in Python and SQL with comfort working directly with large noisy high-frequency datasets.
- Ability to independently build data pipelines and handle raw transaction data rather than relying on pre-curated macroeconomic datasets.
- Strong written communication skills suitable for investor and executive audiences.A practical market-oriented approach focused on accuracy robustness and clear reasoning.
Preferred Qualifications:
- Preferred Experience in hedge funds asset management credit investing central bank research or fintech risk teams.
- Familiarity with consumer credit behavior household finance and unsecured lending cycles.
- Track record of forecasting under uncertainty with measurable performance.
- Experience producing research or insights that influenced investment decisions or risk assessments
$213600 - $296400 a year
The target base salary for this position ranges from $213600/year to $296400/year in San Francisco OR New York.
The base salary range listed for this full-time position excludes commission (if applicable) equity and benefits. The pay range shown on each job posting is the minimum and maximum target for new-hire salaries. Actual pay may be higher or lower depending on factors like skills experience and relevant education or training.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesnt fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race color national origin ethnicity religion or religious belief sex (including pregnancy childbirth or related medical conditions) sexual orientation gender gender identity gender expression transgender status sexual stereotypes age military or veteran status disability or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories consistent with applicable federal state and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability please let us know at emailprotected.
Please review our Candidate Privacy Noticehere.
Required Experience:
IC
Key Skills
- Forecasting
- Python
- Spss
- R
- Regression Analysis
- Stata
- Research Experience
- Statistical Software
- Survey Design
- Calculus
- SAS
- Statistics
About Company
Plaid helps all companies build fintech solutions by making it easy, safe and reliable for people to connect their financial data to apps and services.
