Data Scientist 3
2 days ago
Job Location: Beaverton, OR
Job Duration: 06 Months on W2
Job Description:
Designs, develops and programs methods, processes, and systems to consolidate and analyze structured/unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement. Builds "products" for Analysis. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
Typically requires a Bachelors Degree and minimum of 5 years directly relevant work experience Note: One of the following alternatives may be accepted: PhD or Law + 3 yrs; Masters + 4 yrs; Associates degree + 6 yrs; High School + 7 yrs.
Lead to the accomplishment of key goals across consumer and commercial analytics functions. Work with key stakeholders to understand requirements, develop sustainable data solutions, and provide insights and recommendations. Document and communicate systems and analytics changes to the business, translating complex functionality into business relevant language. Validate key performance indicators and build queries to quantitatively measure business performance. Communicate with cross-functional teams to understand the business cause of data anomalies and outliers. Develop data governance standards from data ingestion to product dictionaries and documentation. Develop SQL queries and data visualizations to fulfill ad-hoc analysis requests and ongoing reporting needs leveraging standard query syntax. Organize and transform information into comprehensible structures. Use data to predict trends and perform statistical analysis. Use data mining to extract information from data sets and identify correlations and patterns. Monitor data quality and remove corrupt data. Evaluate and utilize new technologies, tools, and frameworks centered around high-volume data processing. Improve existing processes through automation and efficient workflows. Build and deliver scalable data and analytics solutions. Work independently and take initiative to identify, explore and solve problems. Design and build innovative data and analytics solutions to support key decisions. Support standard methodologies in reporting and analysis, such as, data integrity, unit testing, data quality control, system integration testing, modeling, validation, and documentation. Independently support end-to-end analysis to advise product strategy, data architecture and reporting decisions.
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