We are seeking a highly skilled and motivated Desk Aligned Engineer to join the research and development team within a large hedgefund focusing on state of the art fundamental & systematic strategies. This role focuses on developing and maintaining real-time data processing systems and analytical tools such as probabilistic graphical models to generate short-term alpha opportunities.
The ideal candidate will have a strong background in software engineering, data analysis, and event-driven architecture, with a passion for leveraging alternative data sources to gain an informational advantage.
You will be working with a modern tech stack including Python (Numpy, and Pandas), Dask, GCP, Airflow, KDB.
Responsibilities:
- Design, develop, and maintain high-performance data pipelines for processing and analyzing real-time market data, news feeds, social media sentiment, podcasts, and other alternative data sources
- Implement and optimize event-driven architectures using technologies like Kafka to capture and react to market events with minimal latency
- Build and deploy scalable analytics solutions on cloud platforms (e.g., GCP) for handling large volumes of structured and unstructured data
- Develop and maintain a knowledge graph to represent complex relationships between market entities and events
- Apply natural language processing (NLP) and other machine learning techniques to extract meaningful insights from unstructured data (text, audio)
- Leverage causal inference methods to assess the impact of events on market prices and identify potential trading opportunities
- Collaborate closely with traders and quantitative analysts to understand their needs and translate them into effective technological solutions
- Continuously monitor and improve the performance, reliability, and scalability of the research infrastructure
Requirements
I. Data Structures
Basic Structures
- Dictionaries (Hash Maps)
- Sets
- Tuples
Advanced Structures
- Ring Buffer
- LRU Cache
- Priority Queue
- Skip List
- B-Tree
- Suffix Tree
- Trie
- Trees
- Graphs
- Heaps
II. Algorithms
Fundamental Algorithms:
- Sorting
- Searching
- Graph Traversal
- Dynamic Programming
Specialized Algorithms:
- Streaming algorithms
- Frequency Estimation
- Finding Frequent Items
- Quantiles and Order Statistics
- Sliding Window Algorithms
- Streaming Graph Partitioning
- Streaming Community Detection
- Graph Algorithms
- Pathfinding Algorithms
- Time Series Analysis
- Anomaly Detection Algorithms
- Forecasting Algorithms
III. Software Engineering Principles
- Object-oriented programming: Classes, inheritance, polymorphism
- Memory management: (garbage collection, optimization)
- Clean code: (readability, maintainability, documentation)
- Testing: (unit tests, integration tests, mocking)
- Version control: (Git and GitHub)
IV. Software Architecture and Design
- Event-driven architecture
- Concurrency and parallelism (Dask, threads, processes, asyncio)
V. Tools and Technologies
Data Science Tools
Big Data and Cloud Computing (GCP) Core services
- Compute Engine
- Cloud Storage
- BigQuery
Deployment and orchestration
Messaging Systems:
Qualifications:
Academically brilliant:
- Demonstrate top-tier performance in a Computer Science & Applied Maths from a leading institution
- Class Rank or GPA (e.g., top 5% of class, 3.8 GPA)
Industry veteran
- Possess at least two years of experience in a hedge fund or trading firm, showcasing your ability to handle complex data challenges and thrive under real-time pressure
- Proactive and driven: Take initiative, assume increasing responsibility, and consistently exceed expectations
- Proven track record of growth: Highlight your career progression and advancements, demonstrating your commitment to excellence and professional development
