drjobs Sr Business Intelligence Engineer WW Installments

Sr Business Intelligence Engineer WW Installments

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1 Vacancy
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Job Location drjobs

London - UK

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Come build the future of FinTech!

The WW Installments team within Amazon Payments (AP) brings together the best of analytics machine learning tech business and finance to deliver for customers across the world. We build the foundational systems and products to enable Amazon customers with installment and related payment methods across the globe. Our mission is to delight our customers by building payment experiences and financial services that are trusted valued and easy to use from anywhere in any way. Our products are growing rapidly and we are continuously adding new marketleading features and launching new customer facing ML solutions. Our team of high caliber engineers scientists developers and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment managing tradeoffs between competitiveness click through rate approval rates customer friction economic profit and loss rates. We leverage the wealth of Amazons information to build a wide range of probabilistic models set up experiments that ensure that we are thriving to reach global optimums and leverage Amazons technological infrastructure to display the right offerings in real time. Our goal is to delight our customers with their purchasing experience and our solutions improve the shopping experience for hundreds of millions of consumers worldwide accordingly. Those of us who love to work with data see this as the pinnacle of opportunities within FinTech and the BNPL/Installment space that you cannot find anywhere else in the world.

As the Sr BIE within WW Installments you will help advance our analytical capabilities and drive the roadmap for our key pillars. This is a leadership role with high degree of influence working with other BIEs DEs and Data/Applied Scientists in one of the worlds largest and most complex data warehouse environments. You should be passionate about working with huge datasets and be someone who loves to bring data together to answer business questions. You should have deep expertise in creation and management of datasets and the proven ability to translate the data into meaningful insights.
The right candidate will possess excellent business and communication skills transform ambiguous business problems to an analytical problem and prioritize work across the team to support business outcomes and develop solutions to key business questions.

Key job responsibilities
This role will be responsible for:
Applying your deep analytic and business skill to extract meaningful insights from large complicated datasets.
Own key executive reports and metrics that are consumed by our VPs and Directors.
Engage business stakeholders in constructive dialogues to convert business problems into logic problems that can be solved with data statistics and/or scripting.
Partner with fellow Data/Applied Scientists to implement scalable automated infrastructure for data extraction processing computation and delivery.
Work closely with data engineering and product management to deliver features to customers.
Identifying new opportunities to influence business strategy and product vision using data.
Support fellow engineers and scientists to deliver analytical projects and build proof of concept applications.
Learn new technology and techniques to support product and process innovation.
Work through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.

Bachelors degree in Data Science Engineering Statistics Mathematics or related field or equivalent experience.
7 year of relevant professional experience working with data and applied analytics.
Experience in programming language (e.g. Python) for automation of data extraction/processing statistical computation and/or web sing. Advanced SQL knowledge for ETLM operations.
Excellent communication (verbal/written) and data presentation skills and demonstrated ability to successfully partner with business and technical teams.
Experience with data visualization using QuickSight Tableau or similar tools.
Demonstrated ability to work with business and technical partners to define requirements and deliver against complex business questions.
Ability to deal with ambiguity and competing objectives in a fastpaced environment.

Masters degree in Business Engineering Statistics Computer Science Data Science Mathematics or related field.
Experience with at least one statistical programming language such as Python Julia or R.
Experience working with test/control methodology timeseries forecast and/or machine learning techniques.
Experience working with AWS big data technologies (e.g. EMR Redshift S3 Glue Kinesis and Lambda).
Prior experience in tech ecommerce retail or finance/banking industry.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit
for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.


Required Experience:

Senior IC

Employment Type

Full-Time

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