Data Scientist - Systematic Data Platform

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

We are seeking a talented Data Scientist to join the Data Science team. The team is responsible for establishing best practices in the data pipeline as well as building large-scale data analytics and modeling for systematic strategies.

What you’ll do 

The Data Scientist will work closely with portfolio managers, data engineering and data operations teams to expand the creation of research-ready datasets and signal generation using statistical and machine learning methods. You will become the domain expert on various financial datasets and conduct EDA to determine data relevance to business questions. You will also help in building out the data science environment that scales the data transformation, curation, analytics and back testing for systematic research. The ideal candidate will be passionate and have practical experience in applying financial modeling and machine learning techniques to data science research for the financial industry.

What you’ll bring

What you need:

• Advanced knowledge of Python, SQL, or other programming languages
• Experience working with large scale data analytics and their applications
• Experience with statistical analysis
• Knowledge of developing quality metrics for structured and unstructured data in ETL/ELT pipeline
• Deep understanding of feature engineering, model training, evaluation and deployment
• Collaborate with investment teams to understand their strategy requirements; build research ready datasets and analytics in the central platform
• Excellent communication skills, both verbal and written
• Degree in a quantitative field such as computer science, data science and financial engineering

We’d love if you had:

• Experience with using data mining and machine learning methods for signal generation
• Exposure to distributed compute platforms such as Spark, Flink and Dask
• Experience with any of the following technologies: Kafka, Docker, Airflow, Athena, Redis
• Experience with back testing
• Knowledge of Financial Instruments such as equity, futures and fixed Income.
• Analytical experience with financial datasets
• Experience with working in the cloud (AWS)