Available for opportunities

Sayid Muhammad
Heykal

Data Analyst & Scientist

Jakarta, Indonesia

Informatics Engineering graduate bridging raw data and executive decision-making through ML research, predictive modeling, and interactive dashboards.

Sayid Muhammad Sayid - Data Analyst and Scientist based in Jakarta

4+

ML Projects

3.68

GPA / 4.00

6000+

Data Processed

Data Analyst

Indonesia Youth Foundation · 2025–Present

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About

Bridging data
and decisions

As a highly motivated Informatics Engineering fresh graduate from the University of Muhammadiyah Prof. DR. Hamka, I've developed strong capabilities in data analytics, machine learning, and data visualization through academic research and organizational experience.

I combine technical rigor—developing high-accuracy exchange rate forecasting models—with business acumen in churn reduction and stakeholder reporting. I'm adept at bridging the gap between raw data and executive decision-making through structured reporting and collaborative project management.

82.11%

MSE Reduction in exchange rate forecasting model

3.68

GPA from University of Muhammadiyah Prof. DR. Hamka

6000+

Raw data used to be preprocessed, analyzed, and visualized

23 yrs

Historical data used in deep learning time-series model

Technical Stack

PythonSQLTensorFlowKerasscikit-learnTableauLooker StudioGoogle SheetsPredictive ModelingClassificationClusteringNLPFeature EngineeringDeep Learning

Core Competencies

Machine Learning90%
Data Visualization85%
Python / SQL88%
Deep Learning78%
Background

Experience &
Education

Work Experience

Data Analyst

2025 – Present

Indonesia Youth Foundation

Deliver data-driven insights to division heads to make decisions more reliable and measurable. Maintain interactive dashboards monitoring project progress against predefined KPI metrics.

Data AnalyticsData VisualizationMember Segmentation
Education

Bachelor of Informatics Engineering

2021 – 2025

University of Muhammadiyah Prof. DR. Hamka

GPA 3.68 / 4.00. Relevant courses: Data Mining, Machine Learning, Artificial Intelligence, Statistics & Probability, Calculus. Conducted literature review on 5 prior studies to identify state-of-the-art forecasting approaches.

  • Designed hybrid CNN-LSTM and CNN-GRU architectures for financial time-series
  • Reduced Mean Squared Error from 0.0019 to 0.00034 — 82.11% improvement
  • GPA 3.68 out of 4.00
Informatics EngineeringMachine LearningResearchData MiningArtificial Intelligence
Contact

Let's work
together

Open to full-time data analyst and data scientist roles, freelance projects, and research collaborations.

Whether it's a data challenge, a modeling project, or a team you're building — I'd love to hear from you.

Send an Email