Job Description

About the Role
Quantitative analytics associate manager is a partner-facing role and is responsible for delivering high impact analytic and data science projects by using analytics, in support of operational risk initiatives across consumer lending. This role supports analytics requirements for Credit Bureau Oversight and Quality reporting along with reporting for Issues Management.
EADS is the central analytics group tasked with solving high-impact business challenges and standing up cutting-edge analytical capabilities to be shared across Wells Fargos analytic community.
We are looking for a high performer to join our team and help us solve challenging and interesting business problems through rigorous data analysis and predictive modeling. In this highly consultative and visible role, you will support development analytic projects from multiple business lines using various technology and techniques ranging from but not limited to supervised, unsupervised and semi-supervised machine learning, deep-learning, NLP, optimization algorithms in both edge nodes and in big data environments (like hortonworks, MapR, Aster etc.)

Responsibilities:
Person would be required to manage team of at least 7 data scientists on various data science projects and work closely with business partners across the organization.
He/She would guide team to perform Data wrangling activities.
He/she would be guiding team in developing statistical/machine learning models using various techniques (supervised, unsupervised, semi-supervised) and technologies including but not limited to SAS, R, Python, Spark, H2O, Aster etc.
Work closely with data engineers, BI and UI specialists and deliver top notch analytical solution for the bank.
Define business problem and translate it into analytical problem.

EssentialQualifications:
BS/BA degree or higher in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis
10 years of relevant work experience.
NLP, Text mining, Image/Voice processing, digital analytics, deep learning, machine learning experience is a must.
Experience with supervise , unsupervised & semi supervise learning
Experience with Deep-learning, Artificial intelligence techniques
Strong programing skill and ability to review codes and help team develop std. and reusable modules.
Expertise in analytic tools : R, Python, SAS etc.
Big Data skills Aster, Hadoop, SPARK, H20 and various big data distributions like Hortonworks and MapR
Strong oral and written communication and consultative skills. Ability to drive projects by working with stakeholders.
Data Engineering Sql ,Teradata, Hadoop, Spark

Exploratory Data analysis Provide exploratory data analysis using Python/R/SAS / SQL
Experience with Databases like oracle , Teradata, Sql server
Advance Excel skills
Data integration and clean up data for the usage
Experience with structured data and semi-structured text or Excel files

Desired Qualifications:
Strong collaboration skills
Output deployment using appropriate technologies (HTML5, Shiny, Django)
Working expertise in Tensorflow, Keras or Pytorch would be added advantage
Ability to translate analytical data into useful business information
Critical thinking and strong problem solving skills
Ability to learn the business aspects quickly
knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.
Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry.
Ability to multi-task and prioritize between projects
Education: BA (Arts)
Industry: Financial Services/Stockbroking, Banking

Skills Required