Quantitative Analytics Sr

Confidential Company  •  Mc Lean, VA

5 - 7 years experience  •  Financial Services

$120K - $130K
Posted on 09/29/17 by Sidwell Miller
Confidential Company
Mc Lean, VA
5 - 7 years experience
Financial Services
$120K - $130K
Posted on 09/29/17 Sidwell Miller

Our Single Family Division is currently seeking a Quantitative Analysis Sr. to implements tools and methods of risk evaluation and monitoring as a member of the Credit Analytics and Reporting team.

Responsibilities include:•Data Engineering:?Cleanse, manipulate and analyze large datasets (Structured and Unstructured data – XMLs, JSONs, PDFs) using Hadoop platform.

?Develop PIG, HIVE scripts to filter/map/aggregate data. Scoop to transfer data to and from Hadoop.

?Manage and implement data processes (Data Quality reports)

•Analysis and Modeling:?Perform R&D and exploratory analysis using statistical techniques and machine learning clustering methods to understand data.

?Develop data profiling, deduping logic, matching logic for analysis

?Big Datalanguages such as R, Python, Spark for analytics and developing dashboards

•Lead a cooperative effort among members of a project team comprised of IT and Business

•Train and mentor staff on Hadoop, R, Python, Spark and otherBig Datalanguages

•Present ideas and recommendations on Hadoop and othertechnologies best use to management

Qualifications :

•Bachelor’s or Master’s degree in Statistics, Economics, Business, Mathematics, Computer Science or related field

•5+ years of experience in processing large volumes and variety of data (Structured and unstructured data, writing code for parallel processing, XMLS, JSONs, PDFs)

•3+ years of programming experience in at least 2 -  R, Python, Spark, Java for data processing and analysis.

•Strong SQL experience

•2+ years of experience – using Hadoop platform and performing analysis. Familiarity with Hadoop cluster environment and configurations for resource management for analysis work

Preferred Skills : •Use of analytical and statistical functions (Standard deviation, decision trees) is preferred.

•Strong quantitative, analytical, and problem-solving skills

•Detail oriented. Excellent communication skills (verbal and written)

•Must be able to manage multiple priorities and meet deadlines

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