Sr. Data Scientist (Customer Analytics)
The Judge Group Inc.

Seattle, Washington

This job has expired.


Location: Seattle, WA
Description:
Sr. Data Scientist (Customer Analytics)

Term: Full Time/Direct Hire

Location: This role is located in Seattle but you are able to work remote in our hub locations if you live in the following areas: Chicago, Denver, Los Angeles, or Atlanta. **

The Sr. Data Scientist (Customer Analytics) will support The Marketing & Customer Analytics Organization for our client which is comprised of data scientists and data analysts responsible for designing and executing analytical solutions to support a variety of marketing and customer-focused initiatives. The Sr. Data Scientist (Customer Analytics) will lead end-to-end development of machine-learning models and algorithms to drive personalization and optimization of the long-term, holistic customer experience, across all customer touchpoints. This role will work closely with multiple partners across the organization to create measurable value by enabling high-quality decisions informed by customer-centric insights into business performance.

Responsibilities/Job Duties

  • Collaborate with our partner teams to create data science products and solutions for stakeholders, translating questions to robust answers efficiently.
  • Apply advanced statistical methods, predictive modeling, and causal inference to discover high-value insights into customer behavior.
  • Extract and prepare large sets of data for analysis; improve existing data resources by building data pipelines using AWS tools and other cloud services.
  • Research, design, and implement production-level, scalable code and algorithms to personalize and optimize the holistic customer experience at Nordstrom.
  • Work within and across teams to develop and deploy data products and data-driven software, driving collaboration and adoption on major data-science initiatives.
  • Partner with engineers and analysts to support ad-hoc analysis; be a force-multiplier for the team in terms of analytical efficiency and quality.
  • Help develop and drive adoption of best practices in all aspects of the Data Science workflow, including intake, design, code review, testing, automation, documentation, reporting, and long-term maintainability.
  • Be a mentor and technical SME for other data scientists and analysts, contributing to team growth in terms of both technical skills and business acumen.

Qualifications/Requirements:
  • 5+ years hands-on professional experience in Data Science and Analytics.
  • Demonstrated success working in a highly collaborative technical environment (e.g., code sharing, using revision control, contributing to team discussions/workshops, and collaborative documentation).
  • Fluency with descriptive and inferential statistical concepts as applied in a business context, including experiment design, analysis of variance, statistical significance, etc.
  • Strong expertise in applying machine learning to a wide variety of business problems.
  • Extensive experience extracting large data sets from various relational and non-relational databases using SQL and big-data tools such as Hive or Spark.
  • Deep familiarity with statistical programming in R or Python.
  • Passion and aptitude for turning complex business problems into concrete hypotheses that can be answered through rigorous data analysis and experimentation.
  • Demonstrated expertise in analytical storytelling and communication of insights to business partners and leadership.

Preferred Qualifications:
  • Experience building, deploying, and maintaining operational models processing a large quantity of data in real-world production environments (example tools: SageMaker, AzureML, Kubernetes).
  • Experience developing and deploying automated data pipelines using cloud services (e.g. AWS).
  • Experience building and deploying data apps using R Shiny, Flask, Dash or similar tools.
  • Strong background and proficiency with explainability and interpretability in machine learning.
  • Experience utilizing machine learning for causal inference and incrementality analysis.
  • Familiarity with e-commerce analytics topics (e.g., targeting and customer segmentation, lifetime value forecasting, and incremental response modeling, to name a few).
  • Demonstrated success in mentoring data scientists and analysts to help them grow in both technical skills and business acumen.
Contact: alemkau@judge.com

This job and many more are available through The Judge Group. Find us on the web at www.judge.com


This job has expired.

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