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Quantitative Science Jobs (NOW HIRING)

Amicis Global

Quantitative Analyst

Jersey City, NJ · On-site

$75 - $85/hr

We are looking for a Data Scientist who can work with the developers and Data Analysts to perform analytics, develop risk and quant models around Insider Risk data. Ultimately, we want to create a ...

CarGurus

Senior Data Scientist

Boston, MA

Advanced degree (or proven experience) in Computer Science, Data Science, Mathematics, or any quantitative science which makes use of advanced data analytics or statistical or machine learning ...

Reddit

Principal Data Scientist, Ads

Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance ...

Reddit

Principal Data Scientist, Ads

Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance ...

T Rowe Price

Quantitative Researcher

Manhattan, NY · Hybrid

S. in a quantitative discipline (Computer Science, Applied Mathematics, Statistics, or related field) * Exceptional analytical and problem-solving skills, blending both quantitative rigor and ...

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How much do quantitative science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for quantitative science in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What is a quantitative science?

A Quantitative Science job involves applying mathematical, statistical, and computational techniques to analyze data and solve complex problems. Professionals in this field work across industries such as finance, healthcare, technology, and research, using models and algorithms to derive insights and make data-driven decisions. They often work with large datasets, employing machine learning, statistical modeling, and data visualization to interpret results. Strong analytical skills and proficiency in programming languages like Python, R, or SQL are commonly required.

What are some typical projects or tasks a quantitative science professional might work on?

A Quantitative Science professional often works on projects such as developing predictive models, designing experiments or surveys, analyzing large datasets, and reporting findings to stakeholders. You might collaborate closely with data engineers, business analysts, and subject matter experts to translate complex data insights into actionable recommendations. It's common to use statistical software and programming languages daily, and project work can range from short-term analyses to long-term research initiatives. The role offers a stimulating mix of independent analytical work and cross-functional teamwork, with opportunities to contribute to strategic decisions within an organization.

What are the key skills and qualifications needed to thrive in the quantitative science position, and why are they important?

To thrive in a Quantitative Science role, you need a strong background in mathematics, statistics, and data analysis, typically supported by an advanced degree in a quantitative discipline. Familiarity with programming languages such as Python or R, statistical modeling software, and experience with data visualization tools are highly valued. Problem-solving, critical thinking, and the ability to communicate complex findings clearly are important soft skills for success. These abilities are essential for accurately interpreting data, informing business or research decisions, and collaborating effectively with multidisciplinary teams.

What does a quantitative science do?

A professional in quantitative science analyzes numerical data to solve complex problems, often using statistical, mathematical, and computational methods. They work in fields like finance, research, or technology, utilizing tools such as programming languages and data analysis software to develop models and inform decision-making.
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Quantitative Science jobs near you
Infographic showing various Quantitative Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 74% Physical, 4% Hybrid, and 22% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Quantitative Analyst

Amicis Global

Jersey City, NJ • On-site

$75 - $85/hr

Contractor

Re-posted 3 days ago

Job description

Title: Quantitative Analyst
Duration: 6+ Months
Location: Jersey City, NJ, 07311
 
Summary:
The Insider Risk team, in partnership with the Information Security Data Operations team, is working on a project to centralize IR data in the Cybersecurity Data Lakehouse (CyberDW). We are looking for a Data Scientist who can work with the developers and Data Analysts to perform analytics, develop risk and quant models around Insider Risk data. Ultimately, we want to create a human risk score for the Insider Risk program. This individual will be adept at ML, AI, and best practices around the new tools in the marketplace.
The Data Scientist / Data Modeler / Quantitative Analyst will play a critical role in advancing the Insider Risk program's detection, scoring, and decisioning capabilities. This role is responsible for designing, building, and continuously improving quantitative models, statistical methods, and analytical frameworks used to identify, assess, and prioritize insider risk across employees, contractors, vendors, and non‐human identities.
The role partners closely with Cyber, HR, Legal, Compliance, Anti‐Fraud, and Enterprise Information Protection to transform complex enterprise data into defensible risk signals, transparent scoring models, and executive‐level metrics that support investigations, governance, and regulatory scrutiny.
Required Skills:
1) Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Economics, Quantitative Finance, Computer Science, or a related discipline.
2) 5+ years of experience in data science, quantitative analysis, or risk modeling, preferably in financial services or regulated industries.
3) Strong experience building statistical or machine‐learning models (regression, classification, anomaly detection, clustering).
4) Proficiency in Python and/or R, with experience in SQL for large‐scale data analysis.
5) Hands‐on experience working with complex enterprise datasets and translating analytics into business decisions.
6) Strong communication skills with the ability to explain complex analytical concepts to non‐technical stakeholders.
7) Experience supporting Insider Risk, Fraud, AML, Cybersecurity, UEBA, or Threat Analytics programs.
8) Familiarity with identity and access data, endpoint telemetry, DLP, email, or collaboration monitoring.
9) Experience with model explainability, governance, and validation in regulated environments.
10) Knowledge of employee lifecycle risk, behavioral analytics, or human‐centric risk modeling.