Senior Data Scientist

Responsibilities

• Create Dashboards using Tableau with Databricks with both visuals (charts, graphs, etc...) as well as tables for end users to slice and dice data to gain insights to various business processes.
• Demo work in small and large virtual settings, obtaining client and end-user feedback to enhance dashboards to meet business requirements
• Within an Agile environment, collaborate with other data scientists, data engineers, quality engineers, business analysts and product owners to ensure solutions meet client needs
• Create and maintain datasets from disparate data sources and provide analysis there of using SQL and Databricks within an Azure Cloud Environment
• Utilizing Tableau in a Databricks Azure Cloud Environment, create dashboards containing visuals (e.g.: charts, graphs) and tables that allow end-users to slice-and-dice data to gain insights to various business processes
• Balance technical data architecture and data flows with end-user UX best practices
• Tell stories with data; educate and instill confidence to motivate stakeholders to act on recommendations
• Engage with Data Engineers to build-out next-level data infrastructure
• Participate in GitHub code reviews and knowledge sharing, especially when building solutions within a business domain that other team members may not work in
• Partner with customers, product owners and business analysts to gather requirements and/or mockup potential dashboard solutions.

Minimum Qualifications

• Ability to obtain and maintain public trust required
• Bachelor’s degree in data science, computer science, analytics or other field.

10 years’ experience in:

• Data and analytics projects using data applications to develop insights from large datasets
• Handling large datasets
• 2 years’ experience in:
• JIRA, GitHub and Confluence
• Databricks
• Statistical software and database management software packages (e.g., R, Python, SAS)
• Cloud platforms
• Relational databases and data warehousing (e.g., OLAP, dimensional modeling)
• Creating dashboards that contain visuals and tables using Tableau with Databricks
• Creating and maintaining datasets from disparate data sources and providing analysis utilizing SQL and Databricks
• Agile methodology.