Sr. Quantitative Analyst
Title: Sr. Quantitative Analyst
Salary: $100-140k
Location: Yakima, WA
Schedule: Hybrid/On-site
Company Profile: A leading food and beverage company is looking to add a Sr. Quantitative Analyst to their team. This person is responsible for developing, maintaining, and applying advanced quantitative models to evaluate business health, financial performance, and macroeconomic trends. The position leverages expertise in financial modeling, econometrics, risk analysis, and forecasting---supported by such tools such as Python, R, SQL, MATLAB, Tableau, Power BI, Bloomberg, and FactSet---to provide actionable insights that influence investment strategy, operational planning, and capital allocation.
The Sr. Quantitative Analyst will Be Responsible For the Following:
- Build and maintain advanced financial models to evaluate company performance and investment opportunities.
- Conduct time-series forecasting, modeling, and regression analysis to project revenue streams, cost structures, capital expenditures, and macroeconomic impacts such as inflation, interest rates, and currency fluctuations.
- Apply risk modeling techniques such as Value-at-Risk (VaR), Monte Carlo simulation, and scenario stress testing to assess business resilience.
- Collaborate with data analysts across departments to ensure data consistency and incorporate operational insights into financial models across departments to ensure data consistency and incorporate operational insights into financial models.
- Develop dashboards and visualization tools (Tableau, Power BI) to communicate findings to executives and the board.
The Sr. Quantitative Analyst Should Have the Following Qualifications:
- Bachelor's Degree
- 3-5+ years experience of advanced analytical modeling experience in the M&A, Company Risk assessments, and Macroeconomic forecasting is desired
- Knowledge of financial modeling and valuation technique, risk modeling and quantitative finance, forecasting and econometric methods, and programming languages
- Manage end-to-end quantitative projects from data acquisition through model deployment and executive presentation
- Balance statistical rigor with practical implementation in fast-paced strategic environments
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