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Quantitative Developer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Quantitative Developer in Boston, MA, lasting 12 months at a competitive pay rate. Key skills include 5+ years in Python, front-end development, SQL, and experience with financial data platforms. Strong problem-solving and communication skills are essential.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
656
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ποΈ - Date
April 4, 2026
π - Duration
More than 6 months
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ποΈ - Location
Hybrid
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π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
Boston, MA
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π§ - Skills detailed
#Libraries #Python #GIT #Data Manipulation #Data Analysis #Datasets #Databases #NumPy #SciPy #Risk Analysis #FactSet #Visualization #Programming #GitHub #SQL (Structured Query Language) #Plotly #Plotly Dash #Pandas #Version Control #Statistics #AI (Artificial Intelligence)
Role description
Title: IT Principal Front-Office Engineer
Location: Boston, MA 02116 (Hybrid-3 days onsite)
Duration: 12 Months
Job Description:
We are seeking a highly skilled and motivated Principal Front-Office Engineer to join our prestigious investment firm. As a Principal Front-Office Engineer, you will serve as the technical lead embedded within the Risk team, driving design and implementation of small-scale applications and proof of concepts that will improve risk analysis, develop AI-enabled workflows, and enhance reporting systems & processes.
You will work closely with risk analysts and investment teams, but your primary focus will be building robust systems and tools that power risk infrastructure, analytics, and decision-ready reporting. Weβre looking for a hands-on software architect and builder who has experience designing systems, rapidly iterating over them and delivering them across the finish line. This role is ideal for a Lead or Senior Engineer who thrives as an individual contributor and wants to drive technical direction without moving into management.
Qualifications
β’ Excellent problem-solving skills, with the ability to think critically, independently, and act with minimal handholding.
β’ Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
β’ Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment.
β’ Full-stack development knowledge with a minimum of 5+ years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets.
β’ Experience with key Python Libraries (pandas, NumPy) required
β’ Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred.
β’ Experience using Version Control (Git) required.
β’ Experience using Agentic Programming tools (Github Copilot, Claude) required.
β’ Proven ability to design, build, and scale application systems in data-rich environments including custom AI tools.
β’ Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront, Moodys), financial databases, and data manipulation techniques preferred. Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred.
β’ Solid understanding of financial markets and multi-asset investment risk domain.
β’ Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics
Title: IT Principal Front-Office Engineer
Location: Boston, MA 02116 (Hybrid-3 days onsite)
Duration: 12 Months
Job Description:
We are seeking a highly skilled and motivated Principal Front-Office Engineer to join our prestigious investment firm. As a Principal Front-Office Engineer, you will serve as the technical lead embedded within the Risk team, driving design and implementation of small-scale applications and proof of concepts that will improve risk analysis, develop AI-enabled workflows, and enhance reporting systems & processes.
You will work closely with risk analysts and investment teams, but your primary focus will be building robust systems and tools that power risk infrastructure, analytics, and decision-ready reporting. Weβre looking for a hands-on software architect and builder who has experience designing systems, rapidly iterating over them and delivering them across the finish line. This role is ideal for a Lead or Senior Engineer who thrives as an individual contributor and wants to drive technical direction without moving into management.
Qualifications
β’ Excellent problem-solving skills, with the ability to think critically, independently, and act with minimal handholding.
β’ Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
β’ Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment.
β’ Full-stack development knowledge with a minimum of 5+ years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets.
β’ Experience with key Python Libraries (pandas, NumPy) required
β’ Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred.
β’ Experience using Version Control (Git) required.
β’ Experience using Agentic Programming tools (Github Copilot, Claude) required.
β’ Proven ability to design, build, and scale application systems in data-rich environments including custom AI tools.
β’ Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront, Moodys), financial databases, and data manipulation techniques preferred. Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred.
β’ Solid understanding of financial markets and multi-asset investment risk domain.
β’ Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics






