| Description :
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Responsibility: Candidate will have experience working with disparate datasets, at scale, within the regulatory limitations. You will design, deploy and maintain innovative solutions to complex data extraction and reporting requirement. We’re looking for a self starter, someone comfortable driving our program forward to accomplish our vision of understanding a holistic view of the customer across many different modalities. - Identify, extract, clean, transform, validate and model data across multiple domains using various technologies and languages
- Utilize new and advanced methods to extract, transform and load data
- Build requirements for, develop and enhance automated processes that provide functional areas with data and information
- Analyze the effectiveness of programs, summarize and present data to enhance future efforts using appropriate statistical methods.
- Document, monitor, and proactively recommend improvement to processes and controls related to area responsibilities while quantifying the impact of changes for leaders.
- Collaborate with cross-functional teams responsible for implementing projects in support of divisional and firm-wide business objectives; occasionally lead cross-functional teams responsible for divisional objectives while following an analytics development lifecycle
Experience Requirement: - Master Degree in Data Science, Analytics, Computer Science Engg., Systems Engg., Statistics with 3+ years of relevant experience
- Experience working with enterprise reporting systems, data analytics.
- Solid understanding of statistical analysis (e.g., hypothesis testing, different types of regressions, elasticities, predictive analysis).
- Experience working as an Analytics Engineer or Data Scientist working with cross functional teams.
- Experience working with data visualization tools and creating data visualization concepts. (Excel, Tableau, or similar)
- Experience using programming/scripting language such as Python or equivalent.
- Experience performing statistical analysis and using tools such as SAS, R, or equivalent.
- Familiarity with AWS RedShift and other distributed computing technologies preferred.
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