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Quant Analytics Jobs in Raleigh, NC (NOW HIRING)

Truist

Conformance Testing Team Lead

Raleigh, NC ยท On-site

Bachelor's degree in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training 2.Six years of related ...

Samprasoft

Full Stack Engineer 60/40 Backend

Durham, NC ยท On-site

As a member of this team, you will partner closely with our investment team on the Fixed Income trading floor, and interact directly with quant analysts, portfolio managers, and traders to build new ...

Duke University

Data Analytics Fellow

Durham, NC ยท On-site

Masters in Mathematics, Computer Science, or another quantitative field. Proficiency with data analysis in Python or R, and SQL. Experience with creating dashboards or other data visualizations ...

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How much do quant analytics jobs pay per year?

As of Jun 10, 2026, the average yearly pay for quant analytics in Raleigh, NC is $115,838.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,300.00 and $148,200.00 per year, depending on experience, location, and employer.

What is the difference between Quant Analytics vs Data Analyst?

AspectQuant AnalyticsData Analyst
Required CredentialsDegree in finance, mathematics, or related fields; often requires programming skillsDegree in statistics, business, or related fields; may require basic programming knowledge
Work EnvironmentFinancial firms, hedge funds, investment banksCorporate, marketing, healthcare, and other industries
Job FocusDeveloping complex models for trading and risk managementInterpreting data to inform business decisions and reporting

Quant Analytics professionals focus on building advanced financial models and algorithms primarily in finance and trading environments. Data Analysts interpret and visualize data to support business strategies across various industries. While both roles involve data handling, Quant Analytics emphasizes quantitative modeling and programming, whereas Data Analysts focus on data interpretation and reporting.

What are the key skills and qualifications needed to thrive as a Quant Analytics professional, and why are they important?

To thrive in Quant Analytics, you need strong quantitative skills, advanced knowledge of mathematics and statistics, and often a degree in fields like mathematics, physics, engineering, or finance. Familiarity with programming languages such as Python, R, or MATLAB, as well as experience with data analysis tools and financial modeling software, is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and conveying insights to stakeholders. These skills and qualities are vital for developing robust quantitative models that support informed decision-making in fast-paced financial environments.

What are Quant Analytics?

Quant Analytics, short for quantitative analytics, refers to the use of mathematical models, statistical methods, and computational techniques to analyze financial data and inform investment decisions. Professionals in this field, known as quantitative analysts or 'quants,' develop and implement algorithms for risk management, pricing, trading strategies, and portfolio management. Quant Analytics is widely used in banks, hedge funds, and investment firms to gain insights from large data sets and optimize financial performance. The role typically requires strong skills in mathematics, programming, and finance.

How do Quant Analytics professionals typically collaborate with other teams within a financial institution?

Quant Analytics professionals often work closely with traders, risk managers, and software engineers to develop, implement, and refine quantitative models. They translate complex data into actionable insights, which may influence trading strategies or risk assessment. Effective communication and teamwork are essential, as quants must present their findings in a way that is understandable and useful to non-technical stakeholders. Collaboration is usually facilitated through regular meetings, code reviews, and joint problem-solving sessions.
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