ZipRecruiter

Log In

2

Quantitative Analyst Part Time Jobs (NOW HIRING)

SCM

Quantitative Research Analyst Internship

Radnor, PA · On-site

Opportunities, including full-time summer internships and part-time work throughout the school year ... Read and analyze academic research or other source material pertaining to anomalies in the global ...

SCM

Quantitative Research Analyst Internship

Radnor, PA · On-site

Opportunities, including full-time summer internships and part-time work throughout the school year ... Read and analyze academic research or other source material pertaining to anomalies in the global ...

EdOps

School Finance Analyst- PART TIME

$23.52 - $32.46/hr

Overview The School Finance Analyst is a part-time role designed for an individual looking to apply ... Quantitative or technical background in either experience or coursework as there are numbers ...

next page

Showing results 1-20

All Jobspart time JobsQuantitative Analyst Part Time Jobs

Quantitative Analyst Part Time information

See salary details

$56.5K

$133.9K

$240K

How much do quantitative analyst part time jobs pay per year?

As of Sep 2, 2026, the average yearly pay for quantitative analyst part time in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What is a quantitative analyst part time?

A Quantitative Analyst Part Time job involves using data analysis, statistical models, and quantitative techniques to assess financial risks, support investment decisions, or optimize trading strategies, typically on a reduced-hour basis. Responsibilities may include programming, data interpretation, and developing predictive models. Part-time roles are common in financial firms, hedge funds, or research institutions, offering flexibility for professionals or students.

What are typical responsibilities and projects handled by a part-time quantitative analyst?

Part-time Quantitative Analysts typically support data-driven decision-making by collecting, cleaning, and analyzing large datasets to identify patterns or trends. You may work on projects such as creating financial models, running simulations, or generating reports for internal teams or clients. Collaboration is frequent with traders, researchers, or risk managers to ensure your analysis aligns with organizational goals. While project scope varies, part-time roles often focus on specific tasks or time-sensitive projects, offering valuable hands-on experience and exposure to real-world data challenges.

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

To thrive as a Quantitative Analyst Part Time, you need strong analytical skills, a background in mathematics or statistics, and proficiency in data analysis, often backed by a relevant degree. Familiarity with programming languages like Python or R, experience with statistical analysis software, and knowledge of financial modeling tools are commonly required. Attention to detail, problem-solving abilities, and effective communication skills are valuable soft skills in this position. These competencies are critical for accurately interpreting complex data, delivering actionable insights, and collaborating efficiently with team members in a dynamic and data-driven environment.

More about Quantitative Analyst Part Time jobs

What cities are hiring for Quantitative Analyst Part Time jobs?

Cities with the most Quantitative Analyst Part Time job openings:

What are the most commonly searched types of Quantitative Analyst jobs?

The most popular types of Quantitative Analyst jobs are:

What states have the most Quantitative Analyst Part Time jobs?

States with the most job openings for Quantitative Analyst Part Time jobs include:

What job categories do people searching Quantitative Analyst Part Time jobs look for?

The top searched job categories for Quantitative Analyst Part Time jobs are:

Quantitative Analyst Part Time jobs near you
Infographic showing various Quantitative Analyst Part Time job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 6% Part Time, and 5% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $133,877 per year, or $64.4 per hour.

Quantitative Analyst Associate (2027)

Philadelphia Phillies - Baseball Operations

Philadelphia, PA • On-site

Part-time

Posted 22 days ago

Job description

Title: Quantitative Analyst Associate
Department: Baseball Research & Development
Reports to: Lead/Senior Quantitative Analyst
Status: Hourly Part-Time Seasonal

Position Overview:

As a Quantitative Analyst (QA) Associate, you help shape The Phillies Baseball Operations strategies by processing, analyzing, and interpreting large and complex data. You do more than just crunch the numbers; you carefully plan the design of your own studies by asking and answering the right questions, while also working collaboratively with other analysts and software engineers on larger projects.

Using analytical rigor, you work with your team as you mine through data and see opportunities for The Phillies to improve. After communicating the results of your studies and experiments to Baseball Operations leadership and executive staff, you collaborate with front office executives, scouts, coaches, and trainers to incorporate your findings into Phillies practices. Identifying the challenge is only half the job; you also work to figure out and implement the solution.

Responsibilities:

  • Conduct statistical research projects and manage the integration of their outputs into our proprietary tools and applications (e.g., performance projections, player valuations, draft assessments, injury analyses, etc.)
  • Communicate with front office executives, scouts, coaches, and medical staff to design and interpret statistical studies
  • Assist the rest of the QA team with their projects by providing guidance and feedback on your areas of expertise within baseball, statistics, data visualization, and programming
  • Continually enhance your knowledge of baseball and data science through reading, research, and discussion with your teammates and the rest of the front office
  • Provide input to database architecture to ensure efficient application of baseball data

Required Qualifications:

  • Deep understanding of statistics, including supervised and unsupervised learning, regularization, model assessment and selection, model inference and averaging, ensemble methods, etc.
  • Meaningful experience programming, using analytical software (Python, R, or similar), and interacting with databases
  • Proven willingness to both teach others and learn new techniques
  • Willingness to work as part of a team on complex projects
  • Proven leadership and self-direction

Preferred Qualifications:

  • Possess or are pursuing a BS, MS or PhD in Statistics or related (e.g., mathematics, physics, or ops research) or equivalent practical experience
  • 0-5+ years of relevant work experience
  • Experience drawing conclusions from data, communicating those conclusions to decision makers, and recommending actions

To be considered, all candidates must submit a response for the prompt below:

In player evaluation, some metrics are highly predictive of future performance but provide limited information about why a player will succeed or fail. Other metrics may be less predictive on their own but can help identify specific strengths, weaknesses, or opportunities for improvement.

Assume you have access to several years of professional baseball data, including traditional statistics, pitch- or play-level tracking data, scouting evaluations, player demographics, injury history, and minor-league level and park context.

In 250 words or less, describe how you would determine which information should be included in a player projection model and which information should instead be used primarily to explain, diagnose, or contextualize the projection. Discuss how you would evaluate a metric that improves historical model accuracy but may not remain stable over time, may duplicate information contained in other variables, or may be difficult to obtain consistently for all players.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.

Apply