I specialized in product management, product ownership, product launch and strategy. My team has designed and constructed seven different product roadmaps which has lead to accomplishing our team goals. My contributions to multiple product roadmaps and three main client projects ensured our company’s success . My team and I collaborated well with other technical teams and prioritized communication and transparency with stakeholders. Main stakeholders have included 400+ analysts, developers, project managers, and engineers to provide exceptional customer service and professionalism. I learn quickly and can jump into any part of the product lifecycle and work to provide business deliverables.
Statistics with R
Statistics with SAS
Biostatistics
Introduction to Data Science
Hypothesis Testing
Business Analysis
β’ Run weekly scrum, strategy and customer meetings
β’ Enable data platform product engineers to move through the product roadmap
β’ Provide support and updates with problems/ changes related to the Data platform
β’ Streamline communication with customers and data engineers
β’ Manage Jira board, releases and tickets
β’ Interview users and relay feedback to the team
β’ Monitor relevant slack channels
β’ Demo UI developments to stakeholders
β’ Work with other data engineering teams to align and advertise data engineering products
β’ Prioritize and drive roadmap features based on deadlines for sprints
β’ Document release notes, user training and feature requests
β’ Set up product design sessions
β’ Own internal products and processes that enable cloud migration
β’ Provide basic solutioning for customers who need ELT tools to move to Snowflake
β’ Lead customers to solutions so they can load, migrate, transform, replicate and catalog their data.
All students who either major or minor in Applied Statistics are required to take Stat 167: Introduction to Data Science. This class requires students to use their skills to collaborate with their peers to work with a real data set. Students tackle statistical problems, visualise data, predict models, and draw conclusions. My fellow team members and I decided to do a shot analysis on Kobe Bryant and determine which variables contributed to his success as a basketball player.
Inputting raw data into SAS and organizing data as well as conducting statistical analyses. Running regression analysis and testing models with different variables to find the best correlation. Primarily worked with emission factors, modified combustion efficiency, and carbon ratios to test different kinds of fuel types and ecosystems that affect smoke and pollution. The research lab’s focus is primarily on compounds present in bio emissions to help improve air quality in the Inland Empire.
– Extract and organize patient data such as medical records, illness history, immunizations, demographics, and medications
– Transfer and update data from NextGen to Epic
– Contribute to a smooth transfer of information between databases
– Troubleshoot and discuss potential problems that could arise with data extraction and analysis team
– Collaborate with nurses, doctors, and medical assistants to ensure quality patient care
– Meet project deadlines and communicate important project dates with the team