Data Scientist - Machine Learning Engineer

Investment Team | Singapore

About this role

We are on the lookout for a Junior to Mid-level Data Scientist - Machine Learning Engineer who will play a key role in enhancing our Machine Learning capabilities, focusing on innovative solutions for insight generation and analytics. As a burgeoning hedge fund startup with a clear vision and commitment to the Asian market. This role is not just about technical expertise but also about aligning with our forward-thinking vision and being at the forefront of shaping our AI strategy.

Key Responsibilities

• Data Analysis & Modeling

  • Develop, implement, and maintain predictive models using traditional machine learning and deep learning techniques.

  • Conduct thorough data analysis to extract actionable insights and perform time series analysis.

• ETL & Data Management

  • Design and develop efficient ETL pipelines to process and manage large volumes of financial data.

  • Ensure data integrity and accuracy across various data sources.

• Cloud Computing

  • Utilize Cloud services to deploy and manage machine learning models in a scalable and reliable manner.

  • Optimize Cloud resources for performance and cost-effectiveness.

• End-to-End Solution Development

  • Engage in the complete lifecycle of model development, from data collection and preprocessing to model deployment and monitoring.

  • Collaborate with cross-functional teams to integrate machine learning solutions into existing systems.

• Innovation & Creativity

  • Explore and implement innovative techniques to solve complex financial problems.

  • Stay current with the latest advancements in machine learning and data science to continually improve and innovate.

• Result-Oriented Approach

  • Focus on delivering high-impact results.

  • Communicate findings and recommendations effectively to stakeholders.

Qualifications 

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.

• 3-5 years of hands-on experience in data science and machine learning.

• Proficiency in Python and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).

• Experience with AWS/GCP/Azure services (e.g., S3, EC2, Lambda, SageMaker, Vertex AI, BigQuery).

• Strong understanding of ETL processes and tools.

• Demonstrated expertise in traditional machine learning algorithms and deep learning techniques.

• Solid experience with time series processing and analysis.

• Excellent problem-solving skills and a creative mindset.

• Strong communication and collaboration skills.