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Senior Big Data Engineer & Data Scientist (Apps Systems Engineer 6)
  • Python
  • Spark
  • PySpark
  • Java
  • SAS
  • Machine Learning
  • Big Data
  • Tensor Flow
  • Excel
  • Database
  • ETL
  • Modeling
  • Hadoop
  • Scala
  • Kafka
  • Deep Learning
  • Unix
  • Keras
Wells Fargo
Summit, NJ 07902
139 days ago
Job Description

Important Note: During the application process, ensure your contact information (email and phone number) is up to date and upload your current resume when submitting your application for consideration. To participate in some selection activities you will need to respond to an invitation. The invitation can be sent by both email and text message. In order to receive text message invitations, your profile must include a mobile phone number designated as “Personal Cell” or “Cellular” in the contact information of your application.

At Wells Fargo, we want to satisfy our customers’ financial needs and help them succeed financially. We’re looking for talented people who will put our customers at the center of everything we do. Join our diverse and inclusive team where you’ll feel valued and inspired to contribute your unique skills and experience.

Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.

Wells Fargo Technology sets IT strategy; enhances the design, development, and operations of our systems; optimizes the Wells Fargo infrastructure footprint; provides information security; and enables continuous banking access through in-store, online, ATM, and other channels to Wells Fargo’s more than 70 million global customers.

The Risk and Finance CIO organization provides technology to several lines of businesses including Risk, Compliance, Finance, Audit and Legal with a combined technology spending in excess of $500+MM annually and is a 1100+ person global organization.

Risk Technology has embarked on an ambitious Risk Transformation program and as part of that we are looking for a senior Big Data Engineer & Data Scientist to join a technology team supporting qualitative and quantitative risk models for multiple LOBs. This individual will be responsible for standing up cutting-edge analytical capabilities, leveraging automation, cognitive and science-based techniques to manage data and models, and drive operational efficiency by offering continuous insights and improvements.

Key Responsibilities:

  • Strong understanding of data science techniques and libraries and their applicability to business problem classes
  • Help in design and implementation of algorithms and tools for analytics and data scientist teams.
  • Use a variety of languages, tools and frameworks to marry data and systems together.
  • Collaborate with modelers, developers, DevOps and project managers on meeting project goals.

Required Qualifications

  • 10+ years of application development and implementation experience
  • A BS/BA degree or higher in science or technology
  • 8+ years of experience with Big Data or Hadoop tools such as Spark, Hive, Kafka and Map
  • 10+ years of experience in one or a combination of the following: data management, data science, Artificial Intelligence (AI) or Machine Learning (ML)
  • 3+ years of experience developing scripts for data extraction, data transformation and loading in a distributed database environment
  • 4+ years of experience delivering ETL, data warehouse and data analytics capabilities on big-data architecture such as Hadoop
  • 6 + years of experience working on cross-organization initiatives
  • 4+ years of development experience with languages such as Python, Java, Scala, or R
  • 4+ years of Low Latency systems development or implementation experience
  • 2 + years of architecture, engineering experience, or a combination of both, with distributed storage and processing technologies
  • 5+ years of experience in software delivery in a large matrixed organization or on a complex system such as AKA, Development, DEVOPS, or QA

Desired Qualifications

  • Excellent verbal, written, and interpersonal communication skills
  • 4 + years of statistical modeling experience using the R programming language
  • Knowledge and understanding of analytical methods used in: statistical analysis, modeling, and reporting
  • Knowledge and understanding of modeling techniques such as ANOVA, Decision Tree, Neural, Logistic, and Monte Carlo
  • SAS programming experience in model implementation, reporting, and complex data manipulations
  • Experience with Tensorflow, Theano or Keras
  • Knowledge and understanding of Machine Learning, Deep Learning, Linear Regression, Models (Tensor Flow)

Other Desired Qualifications
  • 8+ years of experience deploying or managing data pipelines for supporting data-science-driven decisioning at scale
  • 4+ years of experience with python, unix and pyspark programming
  • 4+ years of experience on distributed, high throughput and low latency architecture based on Hortonworks Hadoop Cluster, Private/Public Clouds

Job Expectations

  • Ability to travel up to 10% of the time

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