Python Quant Developer, Research Automation
Dubai
$100k - $200k USD base + bonus
About Muwazana:
Muwazana is a proprietary trading firm building high-performance trading and marketmaking infrastructure for inefficient and underserved global markets.
The firm was founded by ex HRT, Citadel and GSR, and has built a lean global team with
backgrounds across firms including HRT, Jump, SIG, Citadel, Grasshopper and GSR.
The team is highly technical and operates with a flat, collaborative culture across
trading, research and engineering.
Role Overview:
Muwazana is looking for a Python-first Quant Developer to build the research
automation layer used by its trading and quant teams.
You will develop the tools, pipelines and workflows that help researchers and traders
move faster from idea generation through to testing, validation and live trading
handover.
The role sits close to live trading, with a focus on backtesting workflows, market data
analysis, feature generation, signal testing, reporting and reusable Python tooling.
What You’ll Work On:
• Build Python-based tools and pipelines for quant research, backtesting and
strategy analysis.
• Automate research workflows across data ingestion, cleaning, feature
generation, signal testing and reporting.
• Improve the internal research platform so traders and researchers can test ideas
faster and with better visibility.
• Work with market data, order book data, historical trading data and other large
trading datasets.
• Build reusable Python libraries, utilities and frameworks used across the trading
and research team.
• Create tooling for experiment tracking, parameter sweeps, strategy evaluation
and performance reporting.
• Help turn ad hoc research scripts and notebooks into cleaner, repeatable and
production-aware workflows.
• Improve data quality checks, validation processes and monitoring around
research datasets.
• Work closely with production engineers to help bridge the gap between research
outputs and live trading implementation.
• Identify bottlenecks in the research process and replace slow or manual
workflows with scalable systems.
What We’re Looking For:
• Strong Python development experience in a trading, quant, data-heavy or
research-focused environment.
• Experience building research tooling, backtesting frameworks, data pipelines,
analytics platforms or automation around quant workflows.
• Good understanding of the research lifecycle, from data ingestion and feature
engineering through to testing, validation and production handover.
• Experience working with trading datasets such as trades, quotes, tick data, order
book data or similar high-volume financial data.
• Strong software engineering fundamentals, including clean code, testing, version
control and maintainable internal libraries.
• Comfortable working directly with traders and researchers to turn loosely
defined problems into useful tools.
• Strong data manipulation skills using Python libraries such as pandas, NumPy,
Polars, PyArrow or similar.
• Practical, hands-on mindset with the ability to work independently in a lean,
fast-moving team.
• Experience in systematic trading, HFT, market making, proprietary trading, hedge
funds or electronic trading would be highly relevant.
Useful Extras:
• Experience with equities, market making, short-horizon strategies or highfrequency trading workflows.
• Exposure to order book features, microstructure data, execution analysis or
intraday strategy testing.
• Experience with Parquet, Arrow, DuckDB, ClickHouse, kdb+/q, SQL, Kafka or
similar data infrastructure.
• Experience speeding up Python workflows through vectorisation,
multiprocessing, profiling, Numba, Cython, Rust or C++ bindings.
• Familiarity with production trading systems and the handoff from research to live
trading.
• C++ exposure is useful, but this is primarily a Python role.
