- Impactful Contributions: Your work will directly influence key business outcomes, providing a tangible impact
- Innovative Environment: Engage in cutting-edge projects that push the boundaries of data science, offering continuous opportunities for innovation and learning.
- Career Development: Benefit from a commitment to professional growth, with a supportive environment for learning and collaboration with top industry experts.
Responsibilities:
- Develop and refine machine learning models and simulations to inform and improve business decisions and operational efficiencies.
- Establish robust pipelines for the training, validation, and deployment of models across various platforms, ensuring scalability and reliability.
- Design and analyze product experiments using statistical methods to extract meaningful insights that drive product direction and strategy.
- Perform comprehensive data analyses and visualizations to uncover trends, patterns, and insights, answering key business questions.
- Foster a culture of technical excellence through active participation in code reviews, architectural discussions, and continuous learning.
- Translate complex business challenges into analytical frameworks, collaborating with stakeholders to ensure solutions meet their needs.
- Continually monitor and optimize model performance, adapting to new data and evolving business objectives.
- Advocate for a data-driven culture within the organization, effectively communicating findings and insights across diverse audiences.
Requirements:
- A minimum of 2 years of experience as a Data Scientist or an advanced degree (Masters or PhD) in Computer Science, Statistics, Mathematics, or related fields.
- Strong foundation in data science principles, including statistical analysis, modeling, simulation, and optimization, with practical machine learning application experience.
- Proficiency in Python or R, SQL (with a preference for PostgreSQL), and adherence to best practices in software development, such as version control and unit testing.
- Proven track record of applying data science methodologies from concept to production, encompassing data cleaning, feature engineering, model training, and inference.
- Desirable: Experience with geospatial analysis, real-time data processing, and familiarity with industries focused on consumer mobility or dynamic service platforms.
- Additional skills in AWS data analytics services, FastAPI, Flask, Spark, or model deployment are advantageous.
Tyson Jay Recruitment Pte Ltd | EA License No.: 16C7954
Ivan Lim | EA Personnel No.: R1109856
