Data Science with less than a year in Data Analysis & SAP ERP
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Assessing your cultural and operational fit
Results-oriented Information Systems graduate (GPA: 3.61) and BNSP certified specialist with a focus on bridging the gap between operational data and business intelligence. Expert in managing the integrity of transactional data, including promotional settings and customer profiles within SAP ERP, to support organizational workflows. Leveraged advanced analytical techniques in a Data Analysis-centered graduation project to solve business-centric problems. Seeking to transition into a Data Analyst role where I can apply my experience in SAP data architecture and business process optimization to support data-led decision-making.
Dian Nuswantoro University
Bachelor of Information Systems
N/A – June 30, 2025
PT. Batang Alum Industrie
Customer Support Associate
December 15, 2025 – June 14, 2026
Batang, Central Java, Indonesia
Valbury Asia Futures Semarang
Digital Marketing Intern
March 1, 2024 – April 1, 2024
India
Clustering Analysis of Mental Health Clinic Patients
December 1, 2024 – July 1, 2025
Engineered a K-Means clustering model in Python (Pandas, Scikit-learn) by processing and cleaning a dataset of 1000+ patient records. Identified distinct patient segments through data visualization, providing key insights to enhance the clinic's targeted services.
Certified Data Scientist - Intermediate Level (Ilmuan Data Madya)
LSP Universitas Dian Nuswantoro (BNSP)
January 1, 2025 – January 1, 2028
Cultural Fit Analysis
The candidate's involvement in organizational activities (Paskibra) and internships suggests a willingness to engage in diverse roles and collaborate within teams. The academic project and certification align with a data-driven culture. However, the professional experience is primarily in IT support and digital marketing, which, while providing transferable skills, does not directly demonstrate a deep cultural fit for a senior data science role requiring extensive research, model deployment, and complex problem-solving in a dedicated data science team.
Soft Skills & Operational Fit
The candidate demonstrates soft skills such as analytical thinking, problem-solving, attention to detail, time management, team collaboration, and communication, which are beneficial for operational roles. Their experience in financial administration and customer support suggests an ability to work within structured environments and manage tasks effectively. However, the operational experience is not directly in a data science role, which might require a longer ramp-up for specific data science operational workflows.