Seattle, WA Salary:
DOE 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.
- 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.
- 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.
This job and many more are available through The Judge Group. Find us on the web at www.judge.com