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Quantitative Strategy Developer @ MapleCap Partners AG

Pfäffikon SZ, Schwyz, 8808, CHOnsiteFull-time
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About this role

MapleCap Partners AG is a hedge fund specializing in inflation markets. We are looking for a quantitative developer to join our growing team. Founder and Chief Investment Officer of MapleCap, Kamil Szynkarczuk, is an accomplished portfolio manager and leads the young firm.

Job Description

Job Title

Quantitative Strategy Developer

Department Quantitative Team (Front Office)

Location

Pfäffikon SZ, Switzerland

Start Date

January 2027, by arrangement

Duration

Permanent

Workload

Full-time (100%)

Type

On-site (office)

Salary

Competitive

This role is highly autonomous and vertically integrated in the front office. You will collaborate with portfolio managers, other quants, and internal IT. You will own the development of a fixed income systematic strategy platform.

Required Qualifications

Education

Degree from a renowned university in CS, mathematics, physics, engineering or another quantitative discipline

At least 4 years of full-time equivalent studies

Comfortable with probability, statistics, linear algebra, optimization, machine learning

Programming

1+ years of professional experience in python software development

Demonstrated ability to write clean, tested, production-quality python code

Worked on a team of researchers and/or developers

Software Engineering

Evidence of building and shipping production-grade systems

Has written tests, used version control, built CI/CD pipelines, used profiling, used debugging

Collaborated with other developers using code review, issue tracking, and version control

Algorithms

Ability to implement algorithms using data structures and numerical methods

Experience with parallelization of computational workflows

LLM Systems

Demonstrated experience in building and deploying RAG or other LLM-based systems

DevOps

Used docker to build and deploy a service or backend using cloud infrastructure

Databases

Proficient in writing SQL queries including joins and aggregations

Financial Data

Experience in processing time series and other financial market data comprising of millions of individual records

Production Code

Experience translating research or prototypes into robust production code and testing it

Unix Tools

Comfortable developing in Linux and using command-line development tools

Financial Markets

Basic knowledge of fixed income markets: Fixed-income instruments, pricing, yield curves, duration, convexity, spreads, and interest-rate risk

Language

Minimum C1 English proficiency (CEFR)

Effective in communicating technical topics

Advantageous

A curious mindset, analytical thinking, attention to detail, collaborative

Top 10% academic performance or recognition on dean's list

University coursework in finance

Experience in modelling inflation or other macroeconomic time series

Examples of what we could test for

Implementing a specific algorithm as clean python code, including writing tests for it

Developing a solution to an open-ended technical problem

Reasoning through a probabilistic puzzle

Explaining how a fixed income instrument is priced

Debugging a code snippet provided to you

Responsibilities

Take ownership of the buildout of a new systematic trading strategy framework

Collaborate with portfolio managers to define and refine requirements

Use expert software engineering practices and design patterns

Implement core functional blocks such as PnL calculation and analytics

Periodically demonstrate your progress to internal stakeholders

Autonomously manage your backlog priority queue, and timeline

Develop data warehousing requirements for implementation by internal IT

Implement an optimization framework

Build user interfaces as requested by internal users

Employ software engineering best practices for implementing tests and monitoring/observability

Cover production issues during deployment of the systematic strategy

Seek discussions with peers about open problems and proactively ask for help when needed

Benefits

Competitive compensation

Drinks, fruit and snacks in office kitchen

Rapid learning curve within the competitive hedge fund industry

Networking opportunities at industry events

Regular team events

Please apply before COB 10th November 2026

Skills

PythonSQLLinuxDockerMachine Learninglinear algebraProbabilityStatisticsoptimizationFixed IncomeRAGCI/CD

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