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Aid various teams in drawing insight from Indeed's data. Focuses on business facing analytics, predictive modeling, forecasting, and building models. Create interactive dashboards, visualizations, and business tools for use across the organization. Develop reports and analysis templates using Jupyter notebooks and Tableau. Python Coding for reports, dashboards, and visualizations. Use Python, Pandas, and Numpy to help your stakeholders improve their performance, and designing algorithms to decipher deeper why and how questions. Design and maintain dimensional data models in support of BI needs and create ETL pipelines to populate these models. Mine structured and unstructured data using IQL, SQL with large-scale, complex data sets. Participate in strategic and tactical planning discussions and interface with business customers, gathering requirements and delivering complete reporting solutions. Frame complex analytical problems, pulling data, and extracting insights that lead to tangible results.
Align and influence work to achieve goals across multiple stakeholder groups. Deliver small-scope milestones or parts of larger milestones with minimal guidance. Work to understand and clarify the business impact of projects from the beginning and establishes means to measure impacts. Demonstrates fundamental understanding of multiple stakeholder groups functions including in-depth knowledge of at least one. Identifies overlap among requests in a given component. Completes code reviews, leads code reviews with peer, co-owns accuracy and completeness. Documents topic level learnings into common knowledge base. Implements improvements to tools. Suggests and implements improvements within BI to reduce redundancy or standardize metrics. Suggests business process improvements that align with execution on stakeholder goals. Suggests and implements process improvements within components. Recommends best practices and improvements to team growth process. Mentors L1 team members.
Masters degree in Math, Statistics, Computer Science or an equivalent technical field.
Minimum 1 year experience in data science or business analytics.
Minimum 1 year experience in business intelligence/Visualizations using tools including at least one of: Tableau, SAP Businessobjects, Cognos , or Jupyter Notebooks.
Minimum 1 year experience in data engineering (ETL or ELT) with proficiency in building data pipelines using Python.
Minimum 1 year experience with large scale distributed data warehouse solutions including at least one of Teradata, Netezza, Redshift, Vertica, or Postgres.
Minimum 1 year experience using SQL including at least one of: ANSI- SQL, PL/SQL, and T-SQL.
Minimum 1 year experience building Data Warehousing/Reporting solutions with financial, marketing, or sales functions.
Demonstrated ability in classical statistics/probability and time series analysis.
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