Job Description
What you’ll do
- Prepare, clean, and transform process event data for analysis
- Support exploratory data analysis (EDA) to find trends, patterns, and issues
- Create dashboards and reports using tools like Power BI, Tableau, or Plotly
- Work with data scientists to design features and metrics for performance and prediction models
- Help build and maintain data pipelines and process data models
- Integrate data from enterprise systems like SAP, Salesforce, and ServiceNow
- Assist in process mining activities using tools such as Celonis EMS or SAP Signavio
- Support documentation, testing, and quality checks for analytics work
- Learn and apply basics of Responsible AI and Explainable AI (XAI)
Skills & Knowledge Required
- 0–2 years experience in data analytics or data science
- Strong basics of Python and SQL
- Experience with data libraries like Pandas and NumPy
- Exposure to data visualization tools (Power BI, Tableau, Plotly, Matplotlib, Seaborn)
- Basic understanding of machine learning or statistical concepts
- Knowledge of data quality, data wrangling, and feature engineering
- Understanding of event-based/process data (case ID, activity, timestamp)
- Interest in process analytics, AI/ML, and MLOps
Good to Have
- Experience with process mining tools (Celonis, SAP Signavio, PM4Py, ProM)
- Exposure to ETL pipelines and data modeling
- Academic or project experience in operations research or process simulation
Education
- Bachelor’s or Master’s degree in:
- Computer Science
- Data Science
- Engineering
- Mathematics
- or related quantitative fields
Why this role is good
- Work on real enterprise data and business processes
- Learn from experienced data scientists
- Exposure to cutting-edge analytics, AI, and process mining
- Inclusive, growth-oriented, and learning-focused environment
