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Data Analyst I Jobs
Company | Opusing LLC |
Address | United States |
Employment type | CONTRACTOR |
Salary | |
Category | Appliances, Electrical, and Electronics Manufacturing |
Expires | 2023-10-01 |
Posted at | 8 months ago |
Title : Data Analyst I
Location : Bentonville, AR -72712 (100% Remote)
Duration : 12+ Months Contract (Possibility of Extension)
Pay Rate : $28/Hr.
Shift : Shift 1 M-F with 40 hours a week with flexibility schedule.
Overview
The Data Analyst handles all phases of data analysis portions of a customer success engagement within company’s offerings. This position reports directly to the Manager of Data Science. The work includes:
- Performing hands-on advanced data analysis using company’s business intelligence and advanced analytics products as well as other analytics analysis, machine learning, and visualization tools.
- Developing software to support reusable analysis techniques and tools to routinely apply in support of the company’s initiatives.
- Working directly with company’s customers to collect and analyze information in both the Company’s products and related external information in different ways and subsequently presenting and explaining results and insights to Customers’ business teams.
- In addition, utilizing data analysis techniques to recommend operational and system configuration changes, detecting operational trends, and measuring ROI of the Company’s solutions.
- Determining the types of data analysis that best support the increased understanding of the customers’ business goals as they relate to the operation, use, and realization of the business benefits of Company’s products.
Experience Level
Data report analyst generates customized reports and charts as they pertain to the day to day operations and the overall management of services support business. Assigned projects as required using advanced excel and other data related programs.
Please provide top 3 skills needed.
- SQL, Python, Visualization
Responsibilities
- Networking with internal and external stakeholders and product experts, conducting technical meetings to ensure complete coverage of problem and data gathering.
- Developing complex SQL queries, conducting data analysis on new and existing data sources and providing recommendations to improve data quality and related efficiencies.
- Training the customers to use the analytics reporting tools and application.
- Performing testing and verification of analytics created to ensure consistent accurate results.
- Applying cloud data warehouse technologies for analysis of large datasets.
- Analyzing insights, implications and communicating findings (internally and externally) using visually compelling visualizations in Sisense, Looker, IBM Cognos, Tableau, PowerBI, or Qlik Sense with ability to provide clear explanations to business users.
- Performing accurately and thoroughly data scrubbing and loading processes; ensuring data integrity and defining and developing required ELT scripts, queries, and reports.
- Working closely under the supervision of Manager of Data Science for the understanding of the Customer’s analytical problem.
- Designing, coding, implementing, and continuously improving data pipelines, predictive and prescriptive analytical models to help company’s customers maximize ROI.
- Developing, running and evaluating data science and predictive analytics models for detection and analysis of patterns and trends in very large datasets
Qualifications
- Minimum Education: Bachelor’s degree in a STEM field with emphasis on analytics, data Science, or business analytics.
- Exceptional attention to detail and accuracy of data is required.
Desired skills:
- Ability to develop advanced analytic data models.
- Advanced skill in analytics tools, database technologies, and SQL is required.
- Experience using cloud data warehouses (Big Query, Snowflake, etc..).
- Experience and proficiency in data visualization techniques.
- (Sisense, Tableau, Qlik Sense, Looker etc.).
- Prior experience with business intelligence or data visualization software
- Familiarity with basic statistical methods.
- Ability to contribute to the design and development of data pipelines and data warehouses to support the analysis of large-scale data volumes.
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