Tiger Analytics is looking for an experienced AI Solution Engineer with Lean Six Sigma Black Belt certification to join our team. As a leading advanced analytics consulting firm, we help Fortune 500 companies generate valuable insights from their data. With our deep expertise in Data Science, Machine Learning, and AI, we deliver innovative solutions to complex business problems. As a AI Solution Engineer at Tiger Analytics, you will have the opportunity to work on cutting-edge projects, collaborate with cross-functional teams, and drive business value through advanced analytics. The ideal candidate will possess deep knowledge of process improvement methodologies, exceptional analytical skills, and the ability to collaborate across cross-functional teams.
Key Responsibilities
- Analyze organizational processes and systems using task mining and process mining tools
- Develop and implement data-driven process improvement recommendations
- Collaborate with cross-functional teams to design and implement optimized workflows
- Identify automation and AI-driven opportunities to streamline operations
- Lead workshops and discovery sessions with stakeholders
- Create detailed documentation of current and future-state processes
- Support change management and ensure sustainability of improvements
- Deliver measurable outcomes in efficiency, cost savings, and performance
- Bachelor's degree in Industrial Engineering or a related field
- Lean Six Sigma Black Belt certification (mandatory)
- 5+ years of experience in process improvement or industrial engineering roles
- Experience with process mining tools (e.g., Celonis, UiPath Process Mining, Minit)
- Strong analytical, problem-solving, and facilitation skills
- Familiarity with task automation or AI/ML-driven solution design is a plus
- Excellent written and verbal communication skills.
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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