Data Analyst

Deploy models to productive environment and build data pipeline backend for applications as a part of the team.

Use suitable service available on the Amazon Web Service (AWS). Use the servers that can auto-scale during the high traffic or that minimize the cost based on requirements.

Improve existing models, evaluate developed machine learning models and algorithms and metrics to gauge precision as a part of the team.

Build content-based recommender systems to find relevant data from millions of files.

Build data identifiers, including data pipelines to grab and store clauses and search engines to identify appropriate clauses.

Visualize data and assist with data application frontend to demonstrate live models and results using data science methodologies.

Use quantitative analysis to continuously improve technologies, as directed.

Process language data and build machine learning model as a part of the team.

Assist with development and analysis of information, data analytics and modeling efforts utilizing statistic analysis.

Process and analyze data image and video data and build corresponding models as a part of team, and Process finance data and time-series data and build machine learning data as a part of the team.

Explore different models including random forests, support vector machine and neural network combined with traditional time-series models.

Use data clustering algorithms to identify fundamental data and reports.

Use natural language processing tools and algorithms to leverage the use of unstructured data to calculate risk factors.

Requirements: Masters degree in Computer Science, Data Science, Computer Engineering or a closely related field, plus 6 months of experience in the job offered and 6 months of experience in using Python, Linux OS, Jira, Visual Basic, MYSQL, MS SQL, SERVER, R.