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Entry Level Python Quant Jobs (NOW HIRING)

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine ... Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas ...

New

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine ... Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas ...

New

The Hollister Group

Data Scientist - NYC

Boston, MA · On-site

$100 - $200/hr

Bachelor's degree or concentration in a highly quantitative or relevant data science field ... entry-level data science concepts) * Experience writing code in Python * Experience handling ...

Wood Plc

GIS Analyst

Nashville, TN

Overview / Responsibilities Wood is currently recruiting for an entry level GIS Analyst to join our ... Perform GIS database development, qualitative/quantitative analysis, and mapping as a member of ...

Conventus

Marketing Analyst

Westlake Village, CA · On-site

$107K - $132K/yr

Quantitative Processes & DataEngineering - Create and maintain quantitative processes including ... Masters or MBA in related field preferred. * Entry level knowledge of residential mortgage industry ...

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Entry Level Python Quant information

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How much do entry level python quant jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for entry level python quant in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Python Quant vs Entry Level Data Analyst?

AspectEntry Level Python QuantEntry Level Data Analyst
Required CredentialsBachelor's in Math, Finance, or Computer Science; programming skills in PythonBachelor's in Statistics, Business, or related field; proficiency in Excel and SQL
Work EnvironmentFinancial firms, hedge funds, trading desksCorporate, marketing, or consulting firms
Employer & Industry UsageFinance, investment management, tradingVarious industries including retail, healthcare, and tech
Common Search & ComparisonYesYes

Entry Level Python Quants typically work in finance, focusing on quantitative analysis and algorithmic trading using Python. Entry Level Data Analysts work across industries, analyzing data to support business decisions. While both roles require Python skills and a relevant degree, Quants often need a stronger background in math and finance, whereas Data Analysts focus more on data management and reporting.

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What are the most commonly searched types of Python Quant jobs? The most popular types of Python Quant jobs are:
What job categories do people searching Entry Level Python Quant jobs look for? The top searched job categories for Entry Level Python Quant jobs are:
Entry Level Python Quant jobs near you
Infographic showing various Entry Level Python Quant job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Machine Learning Analyst

Machine Learning Analyst

Bracebridge Capital

Boston, MA

$110K - $145K/yr

Other

Posted yesterday

New

Job description

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning team. The team's primary mission is to develop machine learning systems to answer open-ended investment questions and support portfolio management decisions. The team works across the project lifecycle and technical stack, from ideation, understanding and analyzing data, hypothesis generation and testing, and model development all the way through to the deployment and maintenance of models and systems in production. Our work spans statistical modeling, classical machine learning, and modern AI and LLM techniques.

The Machine Learning Analyst's primary responsibility will be to contribute to these efforts alongside other team members. Over time, you will develop the technical and domain expertise needed to take increasing ownership of individual components and ultimately end-to-end projects.

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to translate loosely defined investment ideas into practical tools and models. Successful candidates will have solid programming foundations, be comfortable translating between qualitative and quantitative descriptions of problems and be excited to build data analysis and machine learning systems against the backdrop of portfolio management.

Since the team works closely with trading floor personnel to assist with portfolio management decision-making, an interest in economic and financial markets is essential, but no specific prior experience is necessary.

This role is open to candidates available to begin in the near term, as well as students expecting to complete their undergraduate degree between Fall 2026 and Summer 2027. Start dates will be determined based on candidate availability and, for students, degree completion.

 Responsibilities:

  • Collaborate closely with Machine Learning team members, portfolio managers, and researchers to translate open-ended investment questions into well-defined analytical and machine learning problems
  • Develop and evaluate data-driven machine learning and quantitative models, including simulation- and optimization-based approaches, for investment-related problems
  • Contribute to maintaining existing models and analytic tools in production
  • Over time, take ownership of individual features and components and full projects
  • Clearly document and communicate methods, assumptions, results, and limitations of models to other researchers and trading professionals across the firm
  • Stay current with relevant new techniques and technologies in machine learning and artificial intelligence, particularly as they pertain to finance and investing

Qualifications:

  • Bachelor's degree (or equivalent) in a rigorous quantitative field
  • 0-2 years of experience through industry internships, undergraduate research or thesis, or substantial independent technical projects involving software development, data analysis, or machine learning
  • Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas, scikit-learn, etc), with experience in other languages a plus
  • Experience working with and analyzing data from multiple sources and in multiple formats
  • Familiarity with machine learning and statistical modeling fundamentals, including model evaluation and experimental design
  • Demonstrated ability to independently scope and execute open-ended technical projects
  • Interest in financial markets, intellectual curiosity, and comfort in working on open-ended problems
  • Strong written and verbal communication skills

Current anticipated annual base salary range: $110,000 - $145,000

Base salary within the range will be determined by various factors including but not limited to the individual's experience, skills and qualifications.

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