Data Scientist - Houston, Tx

Customers’ Lives Easier | Teamwork | Self-Motivation | “Get It Done” Attitude | Problem Solver

The Data Scientist will be responsible for developing and implementing analytic solutions, working with vendors on software improvements, and training our team members on how to use the software and data. The Data Scientist should have experience in data analysis, data visualization, and data management, with a focus on customer responsiveness and continuous improvement.

Key Responsibilities:

• Work with vendors to ensure that the TITAN system is up-to-date and meeting the needs of the business, and to identify and implement new features or updates as necessary.
• Work with vendors to ensure that the analytics solutions meet the needs of the plant and that projects are delivered on time and within budget.
• Implement analytics solutions to improve the efficiency and productivity of the manufacturing plant while ensuring customer responsiveness and project visibility.
• Train and support plant staff and office staff to effectively use the TITAN system to improve performance, including data analysis, data visualization, and data management, with an emphasis on customer responsiveness and project visibility.
• Collaborate with other departments to identify and collect data that can be used to improve plant operations and customer responsiveness.
• Support the decision-making process by providing data-driven insights and recommendations to management.
• Develop and maintain data visualization tools, such as charts and graphs, to help the plant’s management team and project managers understand the data and identify trends and patterns.
• Create and maintain documentation related to the analytics solutions and Titan management.
• Monitor and maintain the analytics solutions to ensure they are functioning properly, and that customer responsiveness is maintained.
• Collect and analyze data from various sources within the manufacturing plant and precast projects, such as production data, quality control data, project progress, sales and estimating, and customer feedback.
• Use TITAN to store and organize data, and to create reports and dashboards that provide insights into the performance of the plant and project progress.
• Continuously improve the data analytics process, including the identification of new data sources, the development of new metrics, and the creation of more advanced visualization tools.

Key Performance Indicators (KPIs):

That may be used to measure the performance of Analytics Implementation Specialist:

• Customer satisfaction: The level of satisfaction of the customers with the analytics solutions and the level of responsiveness.
• Training completion rate: The percentage of team members who complete the training on how to use the software.
• Vendor management: The ability to effectively manage vendors to ensure the system is up to date, and new features are implemented as necessary.
• Continuous improvement: The level of effort and success in continuously improving the analytics solutions and Titan system to meet the changing needs of the business.
• Reports generation: The number of reports generated and delivered to management on a regular basis.
• Data accuracy: The percentage of data that is accurate and free of errors.
• Solution adoption rate: The percentage of team members who are actively using the analytics solutions.
• Project completion rate: The percentage of projects that are completed on time and within budget.
• Data visualization: The percentage of important data that is represented visually in the ERM system, such as through charts and graphs.