Senior Data Scientist - Retail Analytics

Our client, a leading national retailer, is seeking a highly analytical and innovative Senior Data Scientist to join their growing team in Seattle, Washington, US . This role offers a hybrid work model, blending remote flexibility with in-office collaboration to drive data-informed decision-making across the organization.

As a Senior Data Scientist, you will play a pivotal role in leveraging vast amounts of retail data to uncover insights, build predictive models, and develop data-driven strategies that optimize sales, enhance customer experience, and improve operational efficiency. You will work with complex datasets, employ advanced statistical techniques, and translate findings into actionable recommendations for business stakeholders.

Key Responsibilities:
Design, develop, and deploy machine learning models and statistical algorithms to address key business challenges in areas such as customer segmentation, demand forecasting, price optimization, inventory management, and churn prediction. Analyze large, complex datasets from various sources (sales, web traffic, loyalty programs, etc.) to identify trends, patterns, and opportunities. Collaborate closely with business stakeholders, product managers, and engineering teams to understand data needs and translate business problems into analytical solutions. Communicate complex analytical findings and recommendations clearly and concisely to both technical and non-technical audiences through reports, presentations, and visualizations. Develop and maintain data pipelines and ETL processes for analytical datasets. Design and analyze A/B tests and other experiments to evaluate the impact of new initiatives. Mentor junior data scientists and contribute to the advancement of the data science practice within the company. Stay current with the latest advancements in data science, machine learning, and artificial intelligence, and identify opportunities for application within the retail context. Ensure the quality, accuracy, and integrity of data used for analysis and modeling. Contribute to the development of data governance policies and best practices.
Qualifications:
Master's or Ph.D. in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field. 5+ years of experience in data science or a related analytical role, with a strong focus on retail analytics. Proficiency in programming languages such as Python or R, and experience with relevant data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch). Strong experience with SQL for data extraction and manipulation from large databases. Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, time series analysis), and experimental design. Experience with big data technologies (e.g., Spark, Hadoop) is a plus. Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib). Excellent problem-solving skills and the ability to think critically and creatively. Strong communication and presentation skills, with the ability to explain complex technical concepts to a business audience. Proven ability to work effectively in a collaborative, hybrid team environment. This is an exciting opportunity to leverage cutting-edge data science techniques to drive significant impact within a leading retail organization. If you are passionate about uncovering insights from data and shaping the future of retail, we encourage you to apply.

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