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(Actualizado 2020-02-21.)Data Scientist, Machine Learning dev
Helsinki, Finland
Nativo English, Fluido Finnish
- AWS AI & DATA (1 year), databases (3 years+)
- Machine Learning (5 years)
- Python (4 years)
Habilidades (29)
Machine Learning
RANDOM FOREST
PERCEPTRON
SUPERVISED LEARNING
OPTIMIZATION
ANOMALY DETECTION
PREDICTIVE ANALYTICS
DATA SCIENCE
AUTOENCODER
DATA VISUALIZATION
Deep Learning
DATA ANALYTICS
STATISTICS
Data Analysis
AWS MACHINE LEARNING
NoSQL
Elasticsearch
SQL
MongoDB
ARCHITECTURE
Natural Language Processing
NLP
DATABASE MANAGEMENT
ECOMMERCE
Hadoop
SW Development
AWS DATA
DATASETS
QUALITY ASSURANCE
Resumen
Highly experienced data scientist and machine learning R&D engineer with international research and industrial
nexperience. Expertise in many areas including Deep Learning, Devops and Cloud Computing. Possesses advanced
knowledge of complex statistical methods and applications. Multilingual, with knowledge of several languages and the
ability to extract abstract problems and translate into achievable tasks to support business decisions and add value to
the business. Developed many effective systems and solutions using machine learning that have resulted in both cost
saving and significant improvements for business. Flexible and adaptable with the determination and ability to take on
any challenge and succeed; works well under pressure to time sensitive deadlines.
Experiencia profesional
2019-04 - Presente
• Application of AWS for machine learning, DevOps (DockerHub, CI/CD)
• Machine Learning Tutor with focus on Python coding, statistical modelling, optimization and deep learning
• Effective AI-based solutions for companies: Ecommerce Personalisation, Blidz Oy
* Design of AI architecture over NoSQL to recommend relevant products to platform users
* Dashboards to quantify user behaviour on the Blidz e-commerce platform
Ecommerce Taxonomy Mapper, Simplifio Oy
* Natural Language Processing based project; Docker container running in Apache Airflow focusing on correlating
e-commerce products to unique taxonomies, with no priori description, over 97% generalization accuracy.
* Application of Transfer Learning from Finnish UlmFit classifier to High Dimensional E-Commerce Mapper
2019-03 - 2019-12
• Development of variational inference models and the applications of Deep Learning (Cell Gene Differential Expression)
in Computational Biology and Genomics using Bayesian Machine Learning.
• Development of study materials on complicated statistical modelling for an upcoming Erasmus programme.
• Collaboration with scientists from different domains from University of Bergen, Southern Denmark, Turku and UEF
2018-11 - 2019-04
• Geospatio-temporal data analysis in innovative real-estate AI start-up
• Software development in Python, MongoDB and Amazon AWS
• Automated machine learning pipelines
• Intelligent independent Python software package for automatic data quality assurance and imputation
2018-09 - 2018-11
• Anomaly detection systems on public tender datasets in R
• Data cleaning and data wrangling in R and Tableau
• Interactive credit scoring business dashboards in Tableau
2017-11 - 2018-09
• Application of machine learning skills in freelance projects for AI companies:
* MindTitan - multivariate time series prediction using Python, Keras on aircraft sensor data
* SixFold - high-performance density-based clustering with fractals using Python on geospatial data
• R Programming Content Development at Beatest
• Online tutor in mathematics, physics, programming, data science
2017-05 - 2017-09
• Clustering methods such as Agnes, CLARA and PAM to detect anomalous clusters in frontend log data signifying click
bots to support business decisions thereby saving approximately 1,300 €/month
• Supervised learning e.g. GLM, random forest to predict and analyse customer churn, resulting in strategy optimisation
and improved customer retention
• Deep learning architecture - eg. Wide & Deep model with Keras and Tensorflow to build a car recommender system,
resulting in improved customer satisfaction and reduced bounce rate.
• Exploratory analysis of log data using Kibana on ElasticSearch clusters for deeper understanding of data features.
• Analytics Database management using Amazon Redshift, MariaDB.
• Analysis of marketing channels and pricing optimization using Spotfire Analytics
Formación académica
2024-11 - 2024-11
2014-01 - 2017-01
2009-01 - 2012-01