Principal Data Scientist

August 17

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Custom Application Development • Microsoft Technologies • Business Requirements Analysis • Microsoft Application Development Competency • Cloud-delivered Solutions

201 - 500

Description

• Leads data-science projects or teams to align with business needs and deliver value. • Brings new value to the business by leveraging your industry experience in terms of where resources and business needs should be allocated. • Leverages extensive experience to drive best practices for discovering, implementing, and maintaining transformative data-science solutions for customers. • Leads data acquisition and understanding efforts for engineering projects using various tools and techniques. • Develops and applies ML frameworks and best practices for scalable and ethical solutions. • Has deep mathematical understanding of statistics and machine learning. • Incorporates best practices for ML modelling with consideration for artificial intelligence (AI) ethics. • Updated knowledge and LLM capabilities in developing own RAG and LLM extensions. • Review, supports and provides best practices for data analysis and modeling techniques. • Ensures selected modeling techniques are appropriate and align with desired project outcomes. • Decide on the next steps (e.g., deployment, further iterations, new projects). • Serves as industry thought leader in data science in Rebate Management. • Provides feedback, drives improvement, and shares knowledge as a data science and industry expert. • Apply deep expertise to drive novel customer experiences, including early access engineering programs. • Applies expertise to mitigate technical customer escalations. • Writes and debugs code for complex projects and leads solution development. • Leads ML and data-science partnerships and IP improvement. • Partners with diverse Enable teams to identify and explore opportunities for the novel application of machine learning (ML) and other data-science tools to above industry. • Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective. • Develops new techniques/methodologies for building solutions for a specific business need based on available data.

Requirements

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) • OR equivalent experience. • 5+ years customer-facing, product-delivery experience, professional services, and/or consulting experience. • Experience working as part of geographically dispersed, diverse, and virtual teams. • Enjoy travel and are comfortable with travel up to 25%. • Demonstrated ability to work with customers and collaborate across company boundaries.