Company Description: We are in Business for People, empowering people in service organizations with innovative Enterprise and Business software solutions.
We've innovated and taken a new approach to delivering ERP that works for people.
Self-driving, adaptive, and intuitive software that is changing the way people work.
Our solutions empower people and deliver a better people experience so people can spend time on meaningful high-value work they live for.
Job Description:
We are looking for an experienced and highly motivated Data Scientist specializing in Artificial Intelligence and Machine Learning to drive the automation of business processes across the LAER lifecycle.
This hands-on role will focus on leveraging data science techniques to reduce manual tasks, streamline workflows, and integrate data across systems to optimize customer outcomes.
You will work closely with cross-functional teams to create, implement, and monitor automation solutions that directly enhance customer experience and operational efficiency.
Key Responsibilities:Data Integration & Automation: Develop and deploy machine learning models to automate processes and integrate customer data across multiple systems of record.Process Optimization: Analyze and improve customer workflows, identifying opportunities for automation to remove manual effort within the LAER lifecycle stages.Predictive & Prescriptive Analytics: Build predictive models to anticipate customer needs, enabling proactive support and decision-making within the Customer Success team.Tool Development: Create tools and frameworks to enable Customer Success Managers (CSMs) to interact with automated insights, reducing repetitive tasks and enhancing customer interaction efficiency.Collaborative Solution Design: Work closely with the Product, Data Engineering, and Customer Success teams to ensure that AI solutions are well-aligned with customer outcomes and business objectives.Continuous Improvement: Regularly evaluate the performance of deployed models and adjust them to ensure they meet evolving customer and business needs.Key Accountabilities:Process Automation Implementation: Design, test, and deploy machine learning models and automation solutions.Performance Monitoring & Adjustments: Track the success of automation tools and adjust algorithms to optimize their effectiveness and align with customer outcomes.Data Accuracy & Integration: Ensure data consistency across systems and work to enhance data integration for a seamless end-user experience.Stakeholder Communication: Regularly report on automation initiatives and impact metrics to stakeholders, demonstrating value and return on investment.Key Metrics for Success:Automation Coverage: Percentage of LAER processes automated with minimal manual intervention required.Reduction in Manual Tasks: Measured decrease in time spent on manual, repetitive tasks by Customer Success Managers (CSMs).
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