InfoTrie (www.infotrie.com) is a Big Data company headquartered in Singapore.
Our flagship solution FinSentS, is a cutting edge Sentiment Analysis and News Analytics engine (www.finsents.com).
It scans the web (news, blogs, social media) and proprietary sources for thousands of stocks, FX, commodities... Sentiment scores are correlated to asset prices to ensure consistency. They can be used a technical indicator or as a quantitative real-time feed (market data) for your algorithms or systems (risk, compliance, …)
You can use our portal, our APIs, our Apps. We can white label our solutions and have our scores and analytics available for your analysts, traders or clients.
We brought in the company decades of expertise on Information Systems, Artificial Intelligence, Financial Engineering & Quantitative Modelling. We see ourselves at the crossroad of these domains empowering access for all to unstructured data.
Responsibilities:
Research and develop automated trading strategies
Analyze and research model performance, optimization, and new market opportunities
Where possible, write papers describing novel work
Requirements:
Strong logical & quantitative aptitude
Experience and knowledge in handling large data sets, and ability to research mathematical and statistical models from such data
Experience of working with scripting languages: Python, R
Prior experience of trading / capital markets
Effective communication skill and ability of independent study and research
Desirable skills:
Previous experience with algorithmic trading platforms
Prior experience of trading based on news event, market sentiment
Working knowledge of forecasting and data mining techniques
Java, Scala
Hadoop, Spark, Storm, Kafka
NoSQL databases: MongoDB, Time Series DB, Redis
Multiple languages (other than English) capability
*A permanent job will be offered according to candidate's performance at the end of internship.
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- Company:
InfoTrie Financial Solutions Pte Ltd - Designation:
Algorithmic Trader - Profession:
IT / Information Technology - Industry:
Finance