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Job Type
Full Time -
Experience
4-6 year -
Salary
$96,900 - $234,300 / Year -
Location
Austin, TX, USA -
Job Function
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Industry
Information Technology -
Qualification
Key Skills
Apache Hive, Data science techniques, Google BigQuery, Google Cloud Platform (GCP), Optimization, Python Programming, PyTorch, R Programming, SPARK Programming, SQL, TensorFlow
Job Description
You will have the chance to be part of a dynamic team in a high-visibility environment, contributing to the creation of an experimentation and measurement sciences center of excellence. Your work will help shape the test design, development, review, and deployment methodology in PayPal's GADS Consumer Marketing organization.
Your way to impact
As a Senior Data Scientist at PayPal, you will develop and implement best practices for experimentation across the organization, driving innovation and accelerating business impact. Working collaboratively with cross-functional teams, you will influence the development of our experimentation platform and guide all experimentation efforts across different business KPIs. Join us and become a key player in shaping the future of experimentation at PayPal, a global leader in online payments and democratization of financial services.
Your day to day
As a Senior Data Scientist you will be responsible for:
- Investigating the current state of the art of experimentation practices and causal inferencing/ML techniques across multiple teams in the GADS Consumer Marketing org and identifying opportunities for upscaling the methodology best practices.
- Identifying improvement opportunities, developing test experimentation prototypes, and benchmarking results to challenge status quo and share the results with the stakeholders.
- Writing scalable code to automate testing frameworks, optimizing for reusability, and getting experimenters onboard with the tools, and capabilities created.
- Collaborating with cross-functional teams, including engineering, product, and marketing, to design, develop, review and track key performance indicators (KPIs) for experimentation.
- Conducting best practices literature review and sharing sessions with the entire org, and providing design review, guidance and sign-off support to stakeholders across the org.
- Conducting experiments to measure these KPIs, as well as deriving actionable insights from the data, to continually improve the technology and drive business outcomes.
What are we looking for
- Advanced degree (MS or PhD) in quantitative science or engineering field (for example: Statistics, Biostatistics, Mathematics, Operations Research, Computer Science, Physics) with a minimum of 5 years of hands-on experience as an individual contributor in the field of experimentation.
- Strong theoretical foundations in probability & statistics, causal inferencing techniques (such as, RCTs, quasi-experimental designs, matching/propensity-based), general testing state of the art (such as, A/B, A/A, multivariate, sequential, split, redirect, bandit-based, personalization, factorial), machine learning.
- Proven expertise in setting up hypotheses to assess consumer behavior, in designing, implementing and deploying tests, in conducting post-hoc analysis, in assimilating best practices for a wide array of design use-cases and communicating the findings in a succinct manner to marketing stakeholders and different experimentation groups.
- Proficiency in building scalable packages/libraries for experimentation, in-depth statistical analysis, causal inferencing and visualization in R and Python.
- Fluency in processing and manipulating large datasets and building data engineering pipelines using technologies such Hive, SQL, BigQuery, or Spark.
- Proficiency in machine learning frameworks and packages, such as TensorFlow and PyTorch.
Nice to Haves
- Experience leading or participating in groups responsible for building out best practices for org-wide experimentation capabilities (such as, experimentation center of excellence).
- Experience participating in ideation and improvement of internal experimentation engineering platforms and working with external A/B testing platforms such as Optimizely, Google Optimize, VWO, Adobe Target or Convert.
- Prior experience working in a cloud-based environment such as GCP.
We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.
Additional Job Description:
Subsidiary:
PayPal
Travel Percent:
0
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PayPal is committed to fair and equitable compensation practices.
Actual Compensation is based on various factors including but not limited to work location, and relevant skills and experience.
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit https://www.paypalbenefits.com.
The U.S. national annual pay range for this role is
$96900 to $234300
Company Info.
PayPalPayPal Holdings, Inc. is an American company operating an online payments system in the majority of countries that support online money transfers, and serves as an electronic alternative to traditional paper methods like checks and money orders.
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IndustryFinTech
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No. of Employees30,900
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Location2211 North 1st Street, San Jose, CA 95131, USA
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Website
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