Quantitative Analyst II - Years of Experience - 3+ (Hiring Salary Range: 75,500 - 113,300) 

Quantitative Analyst III -  Years of Experience - 5+ (Hiring Salary Range: 99,900 -149,900)
Senior Quantitative Analyst -  Years of Experience - 7+ (Hiring Salary Range: 114,900 - 172,400)

Compensation is determined by a combination of factors, including but not limited to education, work experience, and certifications. The actual offer may vary, reflecting the candidate's unique blend of experience, educational background, and skill level.

PURPOSE: 

Dairyland Power Cooperative seeks a talented Quantitative Analyst with extensive analytics and modeling experience to support our Energy Supply and Trading Analytics teams. The Quantitative Analyst will play a pivotal role in providing data-informed strategic insights.

This position is designed for a candidate who thrives in a dynamic environment, possesses a robust technical background, and is adept at building and automating data solutions from the ground up. The ideal candidate has a deep curiosity and passion for the electric utility business, is resourceful, and can translate market insights into actionable tools for traders and leadership.

ESSENTIAL JOB FUNCTIONS:

•    Support senior leadership and key business partners in navigating uncertainties within an increasingly complex, data-driven energy landscape.
•    Apply quantitative insights and analytical tools to enhance decision-making processes in trading, hedging, and portfolio management.
•    Foster collaboration across teams to enhance transparency and efficiency in portfolio analysis.
•    Participate in discovery processes with stakeholders to identify business requirements and expected outcomes.
•    Develop and maintain robust risk models and valuation frameworks for structured products, generation assets, and portfolio hedging strategies.
•    Utilize statistical techniques to improve models, providing insights for market decisions to traders and portfolio managers.
•    Provide advanced data insights for complex business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
•    Lead the interpretation of data analysis and writing reports.
•    Independently source, integrate, and structure internal and external datasets to support analytics and decision-making processes.
•    Build and maintain custom data pipelines and automated workflows, ensuring seamless data accessibility for trading and leadership teams.
•    Develop data analysis tools and predictive models using advanced data analysis techniques and artificial intelligence and machine learning.
•    Maintain dashboards along with other automated reporting tools to ensure quantitative insights are accessible to diverse audiences.
•    Translate complex modeling results into clear, interactive visuals, thereby enhancing transparency and decision-making across the organization.
•    Communicate findings and insights effectively to non-technical stakeholders.

MINIMUM QUALIFICATIONS:

Education & Experience: Bachelor’s degree in analytics, mathematics, statistics, computer science or other related field or equivalent experience. 7+ years of experience owning and managing analytics and modeling tools for strategic utilization. Master’s degree preferred.

Knowledge/Skills/Abilities: Strong verbal, written and interpersonal communication skills, with the ability to interface effectively with individuals at various levels both internally and externally. Ability to manage confidential information. Excellent attention to detail. Strong analytical, planning, problem-solving, and organizational skills. Self-starter with the ability to work independently. Broad IT knowledge across applications development, database management, infrastructure, and operations. Proficiency in the Microsoft technology stack, including Azure, Office 365, and Power Platform. Knowledge of enterprise architecture frameworks (e.g., TOGAF). Understanding of the energy industry or related domains is advantageous.