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:
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
*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:
Quantitative Analyst / Data Scientist - Profession:
IT / Information Technology - Industry:
Finance