Bring data science to life. MLOps-enabled data scientist rooted from mathematics.
M.Sc. Statistics | M.Sc. Economics | Certified AI Engineer, Data Analyst and TensorFlow Programmer..
MLOps Kubernetes Cloud Architect Python torch/keras Data Engineering
A passionate team contributor backeded with agility and innovation.
True love in coding
Track record of responsible programming and nice documentation. Purse high performance, code asethetics and reusability.
True passion in solving real-world problem
Proven efficiency in solving problems with by evaluating desigsn, algorithms and flows. Commit to data janitor and quality control.
True belief in technology
Eager for new challenges, hunger for new knowledge and embrace open source. Having a CI/CD pipelines on my brains.
Authentic Skills from Deliverables
On daily basis, I use containerized environments for Python development and testing, continuously developing Kubernetes cluster, together with IaC (terraform, DevOps pipeline) and supportive toolsets like SQL, Bash, Vue.JS, NodeJS, and data visualization libraries.
Luke AiEye Compute Vision, from zero to production, as the ML engineer.
Delivered in cost-efficient Azure Kubernetes System, with scalable individual modules for Metadata (Django), Batch and Real-time inference (FastAPI), AI-model tuning/training (Pytorch and Keras). Orchestrated data flows, virtual networks, retention policies and embed DevOps plus IaC.
Clinical Data Platform Transformation, as member of pioneer team
Testing, evaluating and transformation the legacy clinical data platform in modern public cloud model. In addition to the tasks like trailing computer vision on CT and automated data modeling, I was significantly involved in multi-cloud infrastructure roots in Kubernetes, messaging systems and private VM-clusters.
Many Successful Data Pipelines, Analytics and Integrations projects
Implemented a data scrambling and anonymization solution using Kubernetes cluster for BaaS(banking as a service) project. During my tenure in pharmaceuticals, at least 3 major regulatory submissions of clinical trial data, where ETL, analytics, modeling and validations are intensive. A few years back, successfully integrated fragmented systems and practices into a uniformed BI platform.
Expertise is rooted from strong academic background and rich expereinces across multiple industry sectors. Philosophy: learn, improve and enjoy from daily work.
Tietoevry | (since Jan 2022)
Bayer AG | (Aug 2021 ~ Dec 2021)
IQVIA, expert service to Novartis | (Dec 2018 ~ Jul 2021)
SantaPark Oy, Rovaniemi (May 2016 ~ Nov 2018)
> M.Sc. Statistics (2018 ~ 2020)
> M.Sc. Business and Economics (2014 ~ 2018)
Bank of Shanghai (Jul 2011 ~ Jun 2014)
Filosofian maisterin tutkinto - tilastotieteen maisteriohjelma
Subject studies completed partially in Finnish (Grade: Very Good/Kiitetävä)
Thesis: Time-Varying Source Separation by Joint Diagonlization on Autocovariances (Grade: Very Good/Kiitetävä)
business_centerM.Sc. Economics and Business Administration132
Master of Science (Economics and Business Administration
Subject studies completed in English(Grade: Very Good)
Thesis: Innovation in Complex Adaptive System: an exploratory study in mobile phone industry (Grade: Good)
library_booksPublications and Researches
AI for Medicine Professional Certificate 3
- AI for Medical Diagnosis
- AI for Medical Prognosis
- AI For Medical Treatment
IBM AI Engineering Professional Certificate 6
- Machine Learning with Python
- Scalable Machine Learning on Big Data using Apache Spark
- Introduction to Deep Learning & Neural Networks with Keras
- Deep Neural Networks with PyTorch
- Building Deep Learning Models with TensorFlow
- AI Capstone Project with Deep Learning
DeepLearning.AI TensorFlow Developer Professional Certificate 4
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- Convolutional Neural Networks in TensorFlow
- Natural Language Processing in TensorFlow
- Sequences, Time Series and Prediction
Google Data Analytics Professional Certificate 8
- Foundations: Data, Data, Everywhere
- Ask Questions to Make Data-Driven Decisions
- Prepare Data for Exploration
- Process Data from Dirty to Clean
- Analyze Data to Answer Questions
- Share Data Through the Art of Visualization
- Data Analysis with R Programming
- Google Data Analytics Capstone: Complete a Case Study
Fundamentals of Parallelism on Intel Architecture 1
- Vectorization, OpenMP, Memory Optimization, Clusters and MPI
Advanced Machine Learning on Google Cloud 5
by Google Cloud
- End-to-End Machine Learning with TensorFlow on GCP
- Production Machine Learning Systems
- Image Understanding with TensorFlow on GCP
- Sequence Models for Time Series and Natural Language Processing
- Recommendation Systems with TensorFlow on GCP
Machine Learning for Trading 3
by Google Cloud, New York Institute of Finance
- Introduction to Trading, Machine Learning & GCP
- Using Machine Learning in Trading and Finance
- Reinforcement Learning for Trading Strategies
Machine Learning with TensorFlow on Google Cloud Platform 5
by Google Cloud
- How Google does Machine Learning
- Launching into Machine Learning
- Introduction to TensorFlow
- Feature Engineering
- Art and Science of Machine Learning
Deep Learning 5
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
Applied Data Science with Python 6
by University of Michigan
- Introduction to Data Science in Python
- Applied Plotting, Charting & Data Representation in Python
- Applied Machine Learning in Python
- Applied Text Mining in Python
- Applied Social Network Analysis in Python