Process Excellence Analyst

Job title:

Process Excellence Analyst

Company:

Bayer

Job description

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.Process Excellence AnalystAbout the RoleAre you passionate about process transformation and data-driven decision making?
Join us as a Process Excellence Analyst, where you will drive impactful process improvements by leveraging data insights and collaborating with technical and business teams. This role is key to advancing and implementing data models that enable effective process optimization across the organization.Your Tasks and Responsibilities

  • Act as a liaison between technical teams, process owners, and SMEs.
  • Translate complex technical concepts into clear, user-friendly language.
  • Use data insights to identify trends and recommend actionable process improvements.
  • Support the implementation of process enhancements based on analytical findings.
  • Assist process owners and SMEs in understanding and utilizing process mining tools.
  • Provide best practice guidance for data analysis and process optimization.
  • Partner with data engineers to develop and refine data models.
  • Gather and relay feedback from stakeholders to improve model usability and effectiveness.

Who you are:

  • Bachelor’s degree in Business, IT, or related field.
  • Experience in process improvement methodologies (Lean, Six Sigma, etc.).
  • Prior experience in data analysis, process modeling, or data transformation.
  • Knowledge of process mining tools (experience is a plus).
  • Strong ability to analyze data, identify trends, and map/model processes.
  • Familiarity with process mining tools and data visualization software.
  • Understanding of data modeling concepts and methodologies.
  • Excellent verbal and written communication skills.
  • Ability to present technical information to non-technical stakeholders.
  • Strong collaboration and relationship-building capabilities.
  • Ability to work effectively in cross-functional teams.

Why Join Us?You will be part of a dynamic team committed to driving process excellence and innovation. You’ll collaborate across diverse functions, contribute to meaningful transformation initiatives, and grow your expertise in data-driven process improvement.YOUR APPLICATIONBayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.Bayer offers the possibility of working in a hybrid model. We know how important work-life balance is, so our employees can work from home, from the office or combine both work environments. The possibilities of using the hybrid model are each time discussed with the manager.
Bayer respects and applies the Whistleblower Act in Poland.
Location: Poland : Pomorskie : Gdańsk || Spain : Cataluña : Barcelona
Division: Enabling Functions
Reference Code: 844852Location:Poland : Pomorskie : Gdańsk || Spain : Cataluña : BarcelonaDivision:Enabling FunctionsReference Code:844852

Expected salary

Location

Gdańsk, pomorskie

Job date

Wed, 07 May 2025 04:10:45 GMT

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