Data Science UA
Опис
About us:
Data Science UA is a service company with strong data science and AI expertise.
Our journey began in 2016 with the uniting top AI talents and organizing the
first Data Science tech conference in Kyiv. Over the past 9 years, we have
diligently fostered one of the largest Data Science & AI communities in Europe.
About the client:
Our client is a quantitative digital assets market-neutral fund specializing
in algorithmic trading across centralized and decentralized markets. The company
designs, builds, and runs high-performance systems that power 24/7 trading
strategies at scale. The edge is in combining advanced quantitative research
with world-class engineering to capture opportunities in the rapidly evolving
digital asset markets.
About the role:
We are looking for a Python Developer with 3–4 years of experience in building
and optimizing high-load, low-latency systems. This is a hands-on engineering
role where you will enhance the execution platform and market data
infrastructure, design and implement connectors for new centralized and
decentralized exchanges, perform latency profiling and code optimization
to achieve maximum throughput and minimal jitter, work with large-scale data
pipelines to support real-time and historical analysis.
Requirements:
— 3–4 years of professional Python development in high-performance, high-load
environments.
— Expert in concurrency and parallel programming (asyncio, multiprocessing,
threading, Dask).
— Proficiency with scientific computing libraries: NumPy, Pandas, SciPy.
— Advanced skills in SQL and NoSQL databases;
— Deep expertise with ClickHouse or equivalent high-volume solutions.
— Strong knowledge of AWS (compute, storage, streaming, orchestration).
— Strong knowledge of messaging brokers (Kafka, RabbitMQ, ZeroMQ).
— Solid foundation in algorithms, data structures, and system design.
— Comfortable with Linux environments, Docker, Git.
Nice to have:
— Knowledge of Go for latency-critical modules.
— Experience with C++/Rust for ultra-low-latency systems.
— Familiarity with time-series analysis, quantitative finance, or crypto
trading.
— Exposure to profiling and debugging tools (perf, flamegraphs, cProfile,
PySpy).
Responsibilities:
— Develop and optimize Python-based trading infrastructure for high-performance
execution.
— Implement and tune parallel and concurrent systems, using frameworks such
as multiprocessing, threading, asyncio, aiohttp, Dask, joblib.
— Build and maintain data pipelines using NumPy, Pandas, SciPy, with storage
in SQL and NoSQL databases (especially ClickHouse, PostgreSQL, Redis).
— Architect and scale systems on AWS, leveraging EC2, S3, Lambda, and related
services.
— Design and integrate with messaging brokers (Kafka, RabbitMQ, ZeroMQ) for
distributed trading workflows.
— Perform latency analysis, profiling, and performance optimization across
trading components.
— Contribute to CI/CD, testing, and best practices in code quality.
The company offers:
— Directly shape the core trading infrastructure of a high-performing crypto
hedge fund.
— Flat, high-impact environment where engineering directly drives P&L.
— Access to cutting-edge problems in latency optimization and distributed
systems.
Data Science UA is a service company with strong data science and AI expertise.
Our journey began in 2016 with the uniting top AI talents and organizing the
first Data Science tech conference in Kyiv. Over the past 9 years, we have
diligently fostered one of the largest Data Science & AI communities in Europe.
About the client:
Our client is a quantitative digital assets market-neutral fund specializing
in algorithmic trading across centralized and decentralized markets. The company
designs, builds, and runs high-performance systems that power 24/7 trading
strategies at scale. The edge is in combining advanced quantitative research
with world-class engineering to capture opportunities in the rapidly evolving
digital asset markets.
About the role:
We are looking for a Python Developer with 3–4 years of experience in building
and optimizing high-load, low-latency systems. This is a hands-on engineering
role where you will enhance the execution platform and market data
infrastructure, design and implement connectors for new centralized and
decentralized exchanges, perform latency profiling and code optimization
to achieve maximum throughput and minimal jitter, work with large-scale data
pipelines to support real-time and historical analysis.
Requirements:
— 3–4 years of professional Python development in high-performance, high-load
environments.
— Expert in concurrency and parallel programming (asyncio, multiprocessing,
threading, Dask).
— Proficiency with scientific computing libraries: NumPy, Pandas, SciPy.
— Advanced skills in SQL and NoSQL databases;
— Deep expertise with ClickHouse or equivalent high-volume solutions.
— Strong knowledge of AWS (compute, storage, streaming, orchestration).
— Strong knowledge of messaging brokers (Kafka, RabbitMQ, ZeroMQ).
— Solid foundation in algorithms, data structures, and system design.
— Comfortable with Linux environments, Docker, Git.
Nice to have:
— Knowledge of Go for latency-critical modules.
— Experience with C++/Rust for ultra-low-latency systems.
— Familiarity with time-series analysis, quantitative finance, or crypto
trading.
— Exposure to profiling and debugging tools (perf, flamegraphs, cProfile,
PySpy).
Responsibilities:
— Develop and optimize Python-based trading infrastructure for high-performance
execution.
— Implement and tune parallel and concurrent systems, using frameworks such
as multiprocessing, threading, asyncio, aiohttp, Dask, joblib.
— Build and maintain data pipelines using NumPy, Pandas, SciPy, with storage
in SQL and NoSQL databases (especially ClickHouse, PostgreSQL, Redis).
— Architect and scale systems on AWS, leveraging EC2, S3, Lambda, and related
services.
— Design and integrate with messaging brokers (Kafka, RabbitMQ, ZeroMQ) for
distributed trading workflows.
— Perform latency analysis, profiling, and performance optimization across
trading components.
— Contribute to CI/CD, testing, and best practices in code quality.
The company offers:
— Directly shape the core trading infrastructure of a high-performing crypto
hedge fund.
— Flat, high-impact environment where engineering directly drives P&L.
— Access to cutting-edge problems in latency optimization and distributed
systems.