Machine learning Manager
Company Name:-
Hudson’s Bay Company
Job Location:-
Bengaluru, Karnataka
Job Summary:-
Job Description
What This Position Is All About:
Reporting to the Director Marketing Strategy and Data Governance, the Data Governance analyst will apply strong expertise in AI to drive personalization and growth sales through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services.
Who You Are:Generate customer-profiling analysis, campaign lists and post campaign analysis in support of various marketing and other CRM initiatives.
Develop and present clear and comprehensive findings/recommendations to leadership on key initiatives.
You also have:Design, develop, test, advocate and build predictive models and segmentationsEffectively communicate the analytics approach and how it will meet and address objectives to business partners.
Advocate and educate on the value of data-driven decision making; focus on the “how and why” .
Identify and develop long-term processes, frameworks, tools, methods and standards.
Coordinate with different functional teams to implement data engineering, models and monitor outcomesAssists in the development of strategic plans.
Understands and analyzes complex business problem, then formulates data-driven hypotheses to drive business value.
Develops experimental design approaches to validate findings or test hypotheses.
Diagnoses and resolves predictive / analytical model performance issues while monitoring system performance and implementation of efficiency improvements.
Applies innovative and best practices to advanced analytics services to ensure high quality standards.
Sets up change control and testing processes to ensure the quality and consistency of ongoing maintenance work.
Develops analytical solutions and makes recommendations based on an understanding of the business strategy and stakeholder needs.
Works with various data owners to discover and select available data from internal sources and external vendorsApplies scripting / programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into well-prepared data sets with multiple levels of granularities (e.
g.
, demographics, customers, products, transactions).
Summarizes statistical findings and
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