Senior Data Scientist

Job Title: Senior Data Scientist

Work Location: Seattle, WA (Hybrid)

Contract Duration: Long Term

Job Summary:

We're looking for a Senior Data Scientist with expertise in Splunk, Adobe Analytics, and advanced modeling techniques to join our Digital Analytics & Intelligence team. You'll work with tools like Python, R, TensorFlow, PyTorch, and AWS SageMaker to build models for forecasting, NLP, and big data optimization. This role bridges digital analytics and predictive modeling to deliver insights across marketing, UX, and operations. It's a high-impact opportunity to turn complex data into strategic business decisions.

Responsibilities:

• Analyze and interpret user behavior using Adobe Analytics and Splunk to drive digital insights and reporting.
• Develop, validate, and deploy predictive models, including forecasting, classification, regression, and clustering models.
• Implement NLP pipelines for processing and extracting insights from textual data (e.g., user feedback, logs, tickets).
• Leverage cloud-native tools like AWS SageMaker for scalable model training, deployment, and monitoring.
• Design and execute big data optimization strategies to improve data processing efficiency and model performance.
• Collaborate with cross-functional teams including marketing, product, engineering, and DevOps to translate business needs into analytical solutions.
• Automate and streamline data workflows using tools like Git for version control and CI/CD best practices.
• Produce clear documentation, data visualizations, and presentations to communicate complex analytical findings to stakeholders.

Skills:

• 3 6 years of experience in data science, machine learning, or a related field.
• Strong experience with Splunk and Adobe Analytics for digital behavior tracking and data aggregation.
• Proficiency in Python and/or R for data manipulation and model development.
• Experience with machine learning frameworks:
• Python: Scikit-learn, TensorFlow, PyTorch, Pandas
• Deep understanding of NLP techniques (e.g., sentiment analysis, topic modeling, named entity recognition).
• Solid foundation in time series forecasting, predictive analytics, and big data handling.
• Experience working with cloud data science platforms, especially AWS SageMaker or similar (Azure ML, Google Vertex AI).
• Knowledge of version control systems like Git and working in collaborative coding environments.
• Strong communication skills to explain complex models and outcomes to non-technical stakeholders.
• Bachelor s or master s degree in computer science, Statistics, Data Science, Engineering, or a related quantitative field.