Data
Senior Data Scientist (Trading)
Job ID: #
A Leading Financial institutions - Remote!
We are seeking a talented individual to join our team as a Senior Data Scientist specializing in predictive analysis and machine learning algorithms within the financial sector. As a Senior Data Scientist, you will play a crucial role in the development and optimization of algorithmic trading systems, leveraging your expertise in equity, derivatives, and FX trading analysis.
**Key Responsibilities**
- Develop cutting-edge systems for predictive analysis and machine learning algorithms.
- Manage the entire lifecycle of algorithm creation, from design and modeling to validation and ongoing optimization.
- Extract and mine valuable data from diverse sources to drive insights and inform decision-making.
- Utilize machine learning tools to select features, build classifiers, and optimize trading models.
- Pre-process both structured and unstructured data to ensure suitability for analysis.
- Enhance data collection procedures to encompass all necessary information for analytical system development.
- Ensure data quality through meticulous processing, cleansing, and validation techniques.
- Analyze large datasets to uncover patterns, trends, and anomalies, deriving actionable solutions.
- Collaborate with the development team to prepare datasets, enhance trading models, and evaluate performance.
- Formulate innovative solutions and strategies to address complex business challenges.
Industry
Location:
Singapore/Remote Asia
Company Size:
Job Type:
Date:
Requirements
- 7 years++ of experience in the financial sector or related fields, with a strong background in equity, derivatives, and FX trading analysis and modeling.
-PHD degree is preferred.
- Knowledgeable about market making and arbitrage in financial markets, with experience in algorithmic trading systems being advantageous.
- Proficient in coding and big data processing (e.g., Python, SQL), with the ability to develop quantitative models from large, complex datasets.
- Experience with hedge funds, mutual funds, trading houses, brokerages, or investment banks is highly desirable.
- Competent in statistical programming languages such as R and Python, as well as database query languages like SQL, Hive, and Pig.
- Strong applied statistical skills, including knowledge of statistical tests, distributions, regression, and maximum likelihood estimators.
- Expertise in machine learning techniques such as k-Nearest Neighbors, Naive Bayes, SVM, and Decision Forests.
- Solid grounding in multivariable calculus and linear algebra for predictive performance and algorithm optimization.
- Skilled in data wrangling to handle imperfections and inconsistencies in data.
- Proficient with data visualization tools such as Matplotlib, ggplot, d3.js, and Tableau for effective communication of insights.