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Job Location: Bangalore/Bengaluru
About this role:
Sr. Quantitative Analytics Specialist 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 Fargo s 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.)
In this role, you will:
- Person would be required to work individually or as part of a team on data science projects and work closely with business partners across the organization.
- He/She would perform Data wrangling activities.
- He/she would be 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.
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Essential Qualifications:
- 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
- ~8 years of experience
- Experience with supervise , unsupervised semi supervise learning
- Experience with Deep-learning, Artificial intelligence techniques
- Strong programing skill
- Expertise in analytic tools : R, Python, Scala, Java
- Big Data skills – Aster, Hadoop, SPARK, H20 and various big data distributions like Hortonworks and MapR
- NLP, Text mining, Image/Voice processing, digital analytics, deep learning, machine learning
- 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
- Business Intelligence
- Tableau, Power BI, Shiny, Dash, HTML5
- Business Analytics
- Data mining and Insights
- Trend Analysis , forecasting and pattern recognition
- Find opportunities in the data and able to communicate to the partners
- Consult with partners to define issues/information needs
- Present findings to multiple levels of management
- Ensure that analyses are delivered on time, while surpassing partner expectations
- Ensure partner transparency throughout the life of the project
- Proactively seek opportunities to increase the value of analysis
- Strong oral and written communication and consultative skills
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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
- Ability to work independently and as part of a team
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