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Data Scientist

Newark, NJ
Our client is looking for a Data Scientist to join our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians and Actuaries tasked with mining our industry-leading internal data to develop new analytics capabilities for our businesses.
The role requires a rare combination of sophisticated analytical expertise; business acumen; strategic mindset; client relationship skills, project management; and a passion for generating business impact.
Contract or contract to hire.


•             Develop and maintain consultative relationships with key business stakeholders
•             Identify, source, transform and join public, proprietary and internal data sources
•             Model large structured and unstructured data sources (e.g. financial transactional, time-series, text, speech/audio and image)
•             Implement advanced statistical methods for prediction and optimization including a wide variety of machine learning technologies (logit, regression, decision trees/forests, boosted models, clustering, etc.) for purposes including explorative analysis, survival analysis, segmentation, prediction and recommendation systems
•             Perform analysis and implement solutions that maximize business impact
•             Prepare and present written and verbal reports to key stakeholders
•             Some domestic travel may be required
•             Execute all aspects of an advanced analytical project under guidance


•             Advanced degree (Masters or Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines
•             Master’s degree graduates should additionally have at least two years of industry experience with responsibility for developing advanced quantitative, analytical, statistical solutions
•             Hands-on experience applying a wide variety of statistical machine learning techniques to real world problems spanning analysis, predictive modeling and optimization on structured and unstructured data
•             Experience using tools such as Python, R, or equivalent for statistical modeling of large data sets
•             Well-developed written and oral communication skills with ability to present complex statistical concepts to non-analytical stakeholders (Excel, Word and PowerPoint are a must)
•             Software engineering experience in C/C++/C#/Java/Scala or similar object oriented or functional languages is highly regarded but not a prerequisite
•             M.B.A. when combined with advanced quantitative degree is highly regarded but not a prerequisite
•             Prior academic or industry research experience is highly regarded but not a prerequisite
•             Prior exposure to financial services or insurance industry may be helpful but is not a prerequisite
•             Strong background in CX, marketing, and digital marketing is required

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