Dinda Novitasari
Email: id[dot][firstnamelastname][at]gmail[dot]com | Jakarta, Indonesia
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A machine learning engineer with more than 3 years of machine learning related work and research experience, who provides the solution for real-world problems by leveraging machine learning (search and recommendation systems).
Dinda Novitasari earned a Master degree from Department of Computer Science and Information Engineering, National Central University. At present, she is a machine learning engineer in the telecommunication industry. Her research interests include machine learning and data mining applications.
A machine learning engineer with more than 3 years of machine learning related work and research experience, who provides the solution for real-world problems by leveraging machine learning (search and recommendation systems). Before starting my career as a machine learning engineer, I spent most of my time as a research student. I researched swarm intelligence, evolutionary computation (scheduling optimisation and recommendation system), machine learning (regression, classification, hyperparameter tuning), information retrieval (document classification), bankruptcy prediction on US company (collaborate with California State University of Fullerton ) during my bachelor and master degree.
- Experiences
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Telkomsel Machine Learning Engineer | 2020-Present
- Collaborated with an external consultant team to productionize more than XX models from XX use cases which targeted over XX Mn users every month, uplifted ARPU by IDR XX Bn, and revenue gross by IDR XX Bn
- Improved existing machine learning pipeline which reduced processing time from XX days to XX hours
- Improved the report availability to XX% by helping the team in automating the dashboard
- Built propensity model with AUC XX, uplifted ARPU by IDR XX Bn, and revenue gross by IDR XX Mn
- Supplied customer value analysis and segmentation for marketing initiative
- Built automated campaign tracking data pipeline for monitoring
part of Digital Prodigy Team
A Job Thing Machine Learning Engineer | 2018-2020
- Built content-based recommender system using Doc2Vec and TF-IDF
- Built data pipeline and warehouse for content and user data using Elasticsearch
- Developed personalised recommendation engines using hybrid algorithms
- Optimised speed and relevancy search engine using Elasticsearch
- Built data pipeline to load data from MySQL to Elasticsearch using Logstash
- Built analytics dashboard using Dash
- Developed multi-language tag recommender using POS-Tag concept
- Developed a classification engine which helps the marketing team reaching out to new customers
- Developed a diagnostic system which helps the product team maintain the job post and product review quality using word embedding, hierarchical clustering
- Developed cross platform job ads push notification system to enhance job application rate
- Skills
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Data Science Skills
Machine Learning, Statistical Analysis, Data Mining, Classification, Clustering
Programming Skills
Matlab, Python
Data Engineering Skills
Web scraping, SQL, NoSQL, Data extraction and transformation
Soft Skills
Project Management
- Tools
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Cloud
AWS EC2
Database
MySQL, Google Firebase, Hive
Framework/ Library
Hadoop, Spark, Kedro, MLFlow, Pandas, Scikit-Learn, NLTK, Spacy, Gensim, Elasticsearch, Logstash, Flask, Redis, Celery, xgboost, SQLAlchemy, Dash
Deployment
Nginx, supervisord, Jenkins, Docker
- Certifications
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- IBM Certified Database Associate DB2 9 Fundamentals
- IBM Certified Solution Designer – Object Oriented Analysis and Design, vUML 2
- IC3 Digital Literacy Certification
- Education
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National Central University - Taiwan
MS in Computer Science and Information Engineering (2016-2018) - 3.88 of 4.00 Supervised by: Prof. Deron Liang
Related courses: Machine Learning (96/100), Introduction to Data Science (90/100), Data Mining on Biological Data (91/100), Intelligent Surveillance (84/100)Brawijaya University - Indonesia
BS in Informatics (2011-2015) - 3.56 of 4.00
Related courses: Calculus (3.5/4.0), Probabilistic and Statistics (4.0/4.0), Discrete Mathematics (4.0/4.0), Advanced Computational Mathematics (3.5/4.0), Pattern Recognition (4.0/4.0), Artificial Intelligence (3.0/4.0), Information Retrieval Systems (4.0/4.0), Data Mining (3.0/4.0), Evolutionary Algorithms (4.0/4.0) - Published Works
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Journals
- D. Novitasari, I. Cholissodin, and W. F. Mahmudy, “Hybridizing PSO with SA for Optimizing SVR Applied to Software Effort Estimation,” TELKOMNIKA, vol. 14, no. 1, 2016.[link]
- D. Novitasari, I. Cholissodin, and W. F. Mahmudy, “Optimizing SVR using Local Best PSO for Software Effort Estimation,” J. Inf. Technol. Comput. Sci., vol. 1, no. 1, pp. 28–37, 2016.[link]
Thesis