Data Scientist (Analytic Consultant 4)
Company: Wells Fargo Bank
Posted on: January 10, 2020
Important Note: During the application process, ensure your contact
information (email and phone number) is up to date and upload your
current resume prior to 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. Data
Management and Insights (DMI) is transforming the way that Wells
Fargo uses and manages data. Our work enables Wells Fargo to
empower and inform our team members, deliver exceptional
experiences for our customers, and meet the elevated expectations
of our regulators. The team is responsible for designing the future
data environment, defining data governance and oversight, and
partnering with technology to operate the data infrastructure for
the company. This team also provides next generation analytic
insights to drive business strategies and help meet our commitment
to satisfy our customers' financial needs. This role is a part of
DMI's Enterprise Analytics and Data Science Team - the central
analytics group tasked with solving high-impact business challenges
for the Enterprise 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, predictive modeling, and design of complex
analytic systems. In this highly technical role, you will support
Enterprise Personalization Program. This initiative is focused on
using ML/AI algorithms to develop personalized customer experience
and marketing programs. As part of the core Personalization Data
Science team, you will collaborate with other data scientists to
generate innovative ideas, create hypotheses, design quantitative
analyses and experiments, build predictive models using ML
techniques, and generate business insight. KEY RESPONSIBILITIES
- Conduct exploratory data analysis, mine data (e.g.,
clustering), and prepare modeling datasets from multiple data
sources. Build, validate, and implement predictive models using
machine learning algorithms (e.g., Random Forests, GBM, neural
networks, SVM, Na ve Bayes Classifier), as well as traditional
statistical modeling techniques (e.g., time series forecasting,
linear and logistic regression).
- Conduct statistical analyses, design in-market experiments,
respond to ad-hoc requests from business partners to
identify/quantify opportunities or address specific questions.
- Present model results and analytic findings, provide insight
and actionable recommendations to business partners to support data
driven and evidence based decision-making.
- Work with complex databases, conduct research to identify data
issues, propose solutions to improve data integrity; perform other
database-related analyses and projects as requested; collaborate
with data engineers to help optimize data retrieval processes to
support ML algorithm automation.
- Utilize emerging analytic and programming techniques to explore
internal and external unstructured and semi-structured data;
recommend how these additional data sources can be used to enhance
existing models and provide additional insight.
- 6+ years of experience in one or a combination of the
following: reporting, analytics, or modeling; or a Masters 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 and 4+ years of experience in one or a
combination of the following: reporting, analytics, or
- 3+ years of SQL experience
- 3 + years of experience using quantitative machine learning
- 3+ years of Python experience
- Extensive knowledge and understanding of research and
- Strong analytical skills with high attention to detail and
- Excellent verbal, written, and interpersonal communication
- 3+ years of statistical modeling experience
- 1+ year of Big Data experience
- Experience with Spark, Hive and Kafka
Other Desired Qualifications
- Advanced degree in quantitative discipline (e.g., Statistics,
Economics, Computer Science, Applied Mathematics).
- Strong programming skills using advanced tools like Python,
SAS, PySpark, H2O, Hive, Scala or SQL with ability to write
efficient code to manipulate data for analytical purposes, conduct
statistical analysis, and develop predictive models. - Ability to
learn new technologies quickly.
- Advanced knowledge of statistical methods (e.g., probability,
multivariate data analysis, regression, PCA, time-series analysis)
and substantial hands-on experience with machine learning
techniques, such as neural networks, random forests, SVM, GBM,
ensemble learning, etc.
- Experience designing experiments and building predictive models
to support marketing initiatives (e.g., propensity models, net lift
models, customer lifetime value models); experience in Financial
Services industry is a plus.
- Strong acumen diagnosing and resolving data issues to ensure
accuracy and completeness.
- Exceptional analytical, critical thinking, quantitative
reasoning, and problem-solving skills with high attention to
details and accuracy. - Ability to solve complex technical problems
to support effective business strategy.
- Prior experience in a role requiring collaboration across
multiple functions within a large, complex organization, strong
business acumen, ability to think strategically and build effective
- Proven ability to drive each project to completion with minimal
guidance while effectively managing multiple projects at a
All offers for employment with Wells Fargo are contingent upon the
candidate having successfully completed a criminal background
check. Wells Fargo will consider qualified candidates with criminal
histories in a manner consistent with the requirements of
applicable local, state and Federal law, including Section 19 of
the Federal Deposit Insurance Act.
Relevant military experience is considered for veterans and
transitioning service men and women.
Wells Fargo is an Affirmative Action and Equal Opportunity
Employer, Minority/Female/Disabled/Veteran/Gender Identity/Sexual
Keywords: Wells Fargo Bank, Gastonia , Data Scientist (Analytic Consultant 4), Professions , Gastonia, North Carolina
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