Data Scientist Intern New York, US; Taipei, Taiwan

Graphen Inc.; New York (NY); On-site; USD 27,552 - 41,328; Full time

Job summary

Graphen Inc. is seeking a Data Scientist/Quantitative Analyst Intern in New York City. In this role, you will collaborate with the AI Trading team to develop innovative AI solutions for the financial and biomedical fields. Responsibilities include developing trading strategies, working with large datasets, and deploying predictive models. Ideal candidates are pursuing or have completed a degree in a quantitative field, have strong statistical skills, and experience in Python or C++. Join us to innovate in the realms of finance and medical AI.

Qualifications

• Currently studying or graduated from a scientific or quantitative field (preferably MS or PhD).
• Extraordinary quantitative and data management skills.
• Proficiency in processing large datasets with statistical packages.
• Software development experience preferably in Python or C++.
• Applied experience with Machine Learning and Big Data technologies.

Responsibilities

• Develop AI trading strategies in various financial markets.
• Work with large data sets and solve difficult analysis problems.
• Prototype, refine, deploy and monitor predictive models.
• Develop operational models for decision making.

Skills

Quantitative and data management skills

Proficiency in Python or C++

Machine Learning

Statistical packages

Innovative thinking

Education

Currently studying or graduated from a scientific or quantitative field (MS or PhD)

Job description

Work with our fast-growing team to solve challenging problems in real-world applications

Graphen builds next-generation Artificial Intelligence (AI) platforms based on graphs to produce full brain functions and create novel industry solutions. Headquartered in New York, the company is currently focused on the Banking AI, Finance AI and Medical AI solutions. Graphen's three main foundations of Ardi AI Platform, Anita AI Trader and Adam AI Robot are built upon advanced R&D of Graphen Technologies in Linked Big Data, Advanced Visualization, Autonomous Learning, Cognitive Feeling, Machine Reasoning, Strategic Thinking, Human Understanding and Prediction. Learn more about Graphen at: http://www.graphen.ai.

Join Graphen, a fast-growing AI company headquartered in the heart of Midtown Manhattan as a Data Scientist/Quantitative Analyst Intern. You will have the opportunity to collaborate with the Artificial Intelligence Trading team and brainstorm new ideas to solve challenging problems in the financial market or in the biomedical field. This position will bring a combination of analytical rigor and innovative algorithm design to create recipes that extract relevant insights from billions of rows of data. This position requires creative thinking with expertise in Machine Learning to help drive business and disrupt the financial industry, or drive medical AI to the next stage.

Responsibilities

• Develop AI trading strategies in various financial market (Forex, stock, ETF, etc.) for finance domain
• Develop AI analyses in genome and/or proteome data in the medical domain
• Work with large data sets and solve difficult, non-routine analysis problems
• Translate unstructured, complex business problems into Machine Learning framework
• Prototype, refine, deploy and monitor predictive models and decisions agents that are used in automation and analysis tasks
• Cross-team collaborations
• Develop operational models to aid financial or medical decision making and applications.

Qualifications

• Currently studying or graduated from a scientific or quantitative field (Preferably MS or PhD)
• Innovative and flexible thinking
• Extraordinary quantitative and data management skills
• Proficiency processing large datasets with statistical packages
• Software development experience as demonstrated through course work, research projects or open source activities, preferably in Python or C++
• Applied Experience with Machine Learning and Big Data technologies
• Previous experience or course work in finance, business, economics, and/or biostatistics is a plus