Quantitative Analyst II

Advisor Group•Scottsdale, AZ

2d•Hybrid

About The Position

Osaic is hiring a Quantitative Analyst II for its Corporate Finance team. Quantitative Analytics partners across the firm to connect data, financial insight, and advisor feedback to practical business decisions. The analyst will work with business leaders to understand performance drivers, identify opportunities to improve the advisor experience, and turn complex questions into clear recommendations. The role owns high-visibility reporting and analysis that informs how Osaic invests, improves services, and supports independent advisors. It also contributes ideas to strengthen the firm’s analytical approach and uses automation and AI-enabled tools to make insights more timely and useful. This is a full-time position based at Osaic’s Scottsdale hub. Osaic is not considering remote candidates and requires employees to work in the office at least four days per week on a hybrid schedule. Compensation is $70,500–$87,000 per year, plus an annual performance-based bonus. Actual compensation depends on job-related factors such as location, skills, licensure, experience, and education.

Requirements

0–3 years of experience using data and analytical methods to solve complex business problems and explain performance outcomes.
0–3 years of experience using SQL and at least one of SAS, Python, or R.
Demonstrated experience using AI-assisted development tools, such as GitHub Copilot or similar tools, to accelerate analysis and code development.
Experience building, automating, and maintaining recurring reports, with strong attention to data quality, controls, and reproducibility.
Strong analytical judgment and intellectual curiosity, including the ability to structure an open-ended question and reach a defensible conclusion.
Experience using data visualization techniques to clearly communicate trends, comparisons, and performance drivers.
Strong written, verbal communication, and presentation skills, including the ability to communicate with senior executives and cross-functional partners.
Strong organization and prioritization skills, including the ability to deliver recurring reports on schedule while advancing ad hoc analyses and workflow improvements.
Bachelor’s degree from an accredited university in a quantitative discipline, such as data science or analytics, mathematics, statistics, physics, engineering, economics, finance, or a related field.

Nice To Haves

Master’s degree in a quantitative discipline.
Familiarity with contribution margin, cost allocation, discounted cash flow, internal rate of return, or recruiting and retention economics.
Familiarity with interpreting profit and loss statements and the independent financial advisor business model, including revenue sources, expense drivers, and the relationship between advisor economics and firm performance.
Familiarity with customer experience analysis and Voice of the Customer methods, including Net Promoter Score, customer satisfaction, survey design and interpretation, and statistical considerations such as sample size, sampling variability, and response bias.
Experience supporting executive-level reporting or business reviews in a fast-paced, highly visible environment.
Demonstrated ability to identify meaningful performance drivers across products, channels, customer segments, geographies, or initiatives.
Strong relationship-building skills and comfort partnering with business, finance, product, marketing, and data stakeholders.
Experience with Power BI or a comparable business intelligence and visualization platform.

Responsibilities

Develop clear, scalable views of performance that explain what changed, where it changed, and the factors driving the result.
Improve reporting workflows, data latency, analytical depth, and stakeholder deliverables using automation and AI-enabled tools.
Investigate performance drivers and business initiatives related to advisor and practice economics, including recruiting, retention, and cost to serve, to inform investment, pricing, and service decisions.
Synthesize structured and unstructured analysis into concise explanations of performance drivers, implications, and recommended next steps.
Partner with business, finance, product, marketing, and data teams to align definitions, validate results, and connect performance trends to business activity.
Present findings to senior executives and other stakeholders, respond to follow-up questions, and translate technical analysis into business-relevant insights.
Maintain rigorous controls so reporting and analysis are accurate, timely, well-documented, and reproducible.