InfoTrie 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:
· Analyze and draw insights from financial data, structured and unstructured
· Research and develop new data mining, text mining algorithms and models
· Improve existing algorithms and models
· Where possible, write papers describing novel work
Requirements:
· Basic knowledge of finance
· Experience with scripting languages: R, Python
· Relational database and SQL
· Linux shell programming: pipes, redirection, process control, etc.
· Statistical and time series analysis
· Machine learning: regression (lasso, ridge, principal component, etc.), clustering, SVM, Neural Nets, etc.
· Regular expressions and text mining techniques
· Effective communication skill and ability of independent study and research
Desirable skills:
· Java, Perl, Scala
· Hadoop, Spark, Storm, Kafka
· NoSQL databases: MongoDB, Time Series DB, Redis
· Distributed search engine: Solr, Elasticsearch
· Multiple languages (other than English) capability
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- Company:
InfoTrie Financial Solutions Pte Ltd - Designation:
Quantitative Analyst / Data Miner - Profession:
IT / Information Technology - Industry:
Finance