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IndustryWeb 2.0, Enterprise
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Quantitative Analyst

at Deep Blue Analytics in New York, NY   —   Apr 06, 2014   |  
Overview
Company Profile
A predictive analytics company with a mission to enable large enterprises to discover actionable trends from unstructured data and act on these trends to enhance growth and preempt failure. We do this by applying our experience in data analysis to develop predictive tools that are useful across functional lines.

The firm was founded by a group of professionals who come from a variety of backgrounds - venture capital, systematic trading/hedge fund management, software product development, artificial intelligence and academia. The team has a core competency in machine learning methods, data mining, statistical analysis and software development. We have a strong client foot print in the Financial Services and Insurance verticals and are expanding the team to support the growth.

Responsibilities
The Quantitative Analyst will work closely with the data science and business development teams as well as senior management in the design and development of predictive models and innovative tools. Types of work include gathering and transforming data into forms conducive for machine learning, implementing known and novel machine learning algorithms, implementing predictive models to interface with client technologies and working on the development of proprietary tools. The candidate must be highly motivated and someone who can take initiative to explore techniques beyond those in narrowly specified tasks.

Contact: Please send your resume and a cover letter to: hiring@deepblueanalytics.com

Deep Blue Analytics is an Equal Opportunity Workplace
Experience
Masters Degree in computer science or in a relevant field with programming knowledge/experience (e.g. statistics, economics, and mathematics) OR Bachelor Degree in computer science with a demonstrated 1-2 years work experience (internships will be counted toward the experience)
Strong programming expertise in a traditional language (e.g. Java, C++, C#, etc.) as well as in a scripting language environment (e.g. Python, Perl, Ruby, etc.)
Experience with Linux and Windows based environments
Knowledge of databases and SQL
A fast learner and someone with the drive to work in a start-up environment
An intuition for working with data and using data to extract insights and develop predictive models
Someone with effective communication skills and the ability to prototype new ideas and present the results quickly.
Skills
One or more of the following considered a PLUS:
An understanding of machine learning algorithms (decision trees, random forest, support vector machines, etc.)
Experience with linear models
Industry experience building predictive models
Experience with statistical packages (R, Matlab) and machine learning tools (e.g. Salford Predictive Miner, Weka)
Experience evaluating statistical models and/or machine learning models
Experience with feature reduction, clustering, data segmentation, uni/bi-variate analysis
Experience creating data visualizations
Education
•Masters Degree in computer science or in a relevant field with programming knowledge/experience (e.g. statistics, economics, and mathematics) OR Bachelor Degree in computer science with a demonstrated 1-2 years work experience (internships will be counted toward the experience)
Compensation
DOE
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