Senior Data Scientist, Operations Research

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What you'll do...

Position: Senior Data Scientist, Operations Research 

Job Location: 1375 Crossman Avenue, Sunnyvale, CA 94089 

Duties: Develop highly scalable data science solutions including building supply chain models, performing data processing, and overseeing end-to-end data modeling pipelines. Automate the variant grouping pipeline, design database structure, and establish a streamlined data flow from diverse input sources using cloud computing services and database management software. Leverage advanced statistical analysis, machine learning, simulation, and optimization techniques to identify patterns, trends, and correlation within data, thereby facilitating strategic, long-term supply chain network design. Design and maintain visualizations to effectively communicate intricate supply chain data findings to non-technical stakeholders. Collaborate cross-functionally with teams in operations, product, finance, and engineering to identify optimization opportunities and provide valuable insights. Develop intelligent solutions for Network transformation, such as capital allocation, flow optimization, and monetization strategies. Design user-friendly interface and develop interactive web applications, including facilitating self-service for stakeholders, enabling seamless model accessibility, and streamlining the execution of complex model workflows. Employ heuristic analysis to determine the potential impact of initiatives, and apply causal inference methodologies to design experiments, including A/B testing, synthetic control, and difference-in-differences techniques, to evaluate strategic initiatives and measure their market influence. Utilize geospatial systems and tools to build geometric database for last mile use cases and develop frameworks for last mile optimization. Create dynamic visualizations to effectively communicate geographic and data-driven insights to stakeholders. 

Minimum education and experience required: Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), or related field; OR Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), or related field and 2 years of experience in an analytics or related field. 

Skills required: Experience designing and implementing database structures using SQL, Python, and GCP. Experience building machine learning models using Python and Scikit-learn. Experience building optimization models using CPlex. Experience conducting statistical analysis to interpret data using Python and linear regression. Experience visualizing model results using Python, Seaborn, Folium, and Tableau. Experience executing simulation and deploying REST API. Experience developing web applications using Django and StreamLit. Experience creating dynamic visualization using Kepler and Leafmap. Experience designing experiments using causal inference methods, including A/B test, synthetic control, and difference-in-differences. Experience with geospatial indexing systems, including the uber H3 geospatial system. Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills.