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Data Scientist | ML Engineer | Exploring Quantitative Finance
Results-driven professional with a unique blend of academic backgrounds, including a Theoretical Physics degree, graduate studies in AI and a finance-focused MBA, complemented by hands-on experience as Machine Learning Engineer / Data Scientist. Proficient in data analysis, data-centric machine learning and data-driven decision-making. Strong analytical thinker, resourceful problem solver, and effective communicator. Eager to leverage a diverse skill set to contribute to innovative research and business initiatives. Graduated with First Class Honours in Theoretical Physics and MBA cum laude.
TBS Education
Exchange Semester - Non Degree, International Finance
January 1, 2021 – January 1, 2021
Universitas Gadjah Mada
Master of Business Administration - MBA, Finance, General
January 1, 2019 – January 1, 2022
The University of Edinburgh
Postgraduate Certificate - PGCert, Artificial Intelligence
January 1, 2016 – January 1, 2017
Stanford University
Stanford Summer Session - Non Degree, Computer Science and Political Science
January 1, 2014 – January 1, 2014
Swansea University / Prifysgol Abertawe
Bachelor of Science (with Honours) - BSc (Hons), Theoretical Physics
January 1, 2012 – January 1, 2016
Dua Empat Tujuh, PT (SOLUSI247)
Lead Data Scientist
October 1, 2024 – Present
Dua Empat Tujuh, PT (SOLUSI247)
Data Scientist
October 1, 2023 – Present
Freelance
Data Scientist
March 1, 2023 – September 1, 2023
Yogyakarta, Indonesia · Remote
Nomura Research Institute Indonesia
Machine Learning Engineer
January 1, 2022 – December 1, 2022
Jakarta, Indonesia · Remote
Self-employed
Consultant (Coffee Grader & Judge)
June 1, 2018 – July 1, 2019
Swansea University
Physics Student Ambassador
October 1, 2013 – June 1, 2016
Greater Swansea Area · On-site
Data-Driven Portfolio: Implementation of Data Science Techniques in Portfolio Management
May 1, 2021 – January 1, 2022
Masters’ thesis on implementation of data science techniques in stocks portfolio management. Tackling each three essential stages of portfolio management; construction, optimisation and assessment, using methods such as clustering, principal component analysis and Monte Carlo simulation. Upon completion, the thesis was promoted by the board of examiners to be published and currently in progress.
Deep Neural Network for CIFAR-10 and CIFAR-100 Image Classification
February 1, 2017 – March 1, 2017
Implementation project on deep convolutional neural network for image classification using TensorFlow. Built a model that uses both wide and deep learning. Utilised AWS EC2 Spot Instances to provide cost efficient GPU-enabled, cloud-based Jupyter notebook. Compared different regularisation techniques to optimise the result. Achieved an accuracy of 70.4% on validation sets for CIFAR-10.
One-Way Quantum Computation: An Introduction to Measurement-Based Quantum Computing
January 1, 2016 – April 1, 2016
Final year dissertation project on the recently discovered model of quantum computing. The main objective is to study whether an adaptive method to measurement based quantum computing could be on par in efficiency and accuracy in comparison to the more widely used quantum circuit model.
PH312 Group Project: Particle Identification from LEP and Atmospheric Neutrinos from Super-Kamiokande
September 1, 2015 – November 1, 2015
Required group project for the completion of the experiment module, PH312, on identifying particle collision events data from LEP (CERN) and identifying atmospheric neutrinos events from Super-Kamiokande.
Amazon Web Services Cloud Practitioner
Amazon Web Services (AWS)
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse educational background (Physics, AI, MBA, Computer Science, International Finance) and varied project experience (quantum computing, particle identification, financial modeling, image classification) indicate a broad intellectual curiosity and adaptability. The experience in different roles, including a break to work as a coffee grader, suggests a willingness to explore different paths and a potentially well-rounded personality. The transition from Data Scientist to Lead Data Scientist and covering ML Engineer roles at SOLUSI247 shows growth and a proactive approach, aligning with a dynamic work culture. The target role of ML Engineer aligns well with recent professional experience and academic pursuits.
Soft Skills & Operational Fit
The candidate's experience as a Lead Data Scientist and Interim Business Development Team Lead suggests strong leadership, project management, and communication skills. The Physics Student Ambassador role also indicates good interpersonal skills. The diverse educational background and project work suggest adaptability and a strong learning aptitude, which are beneficial for operational fit.