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Andranik U.
Machine Learning Engineer
Andranik is a highly skilled Machine Learning/MLOps Engineer with six years of extensive experience in the commercial sector. His career encompasses roles as a research analyst, data expert, and educator, showcasing his diverse expertise across various industries.
Andranik excels in designing and deploying machine learning models and has demonstrated his ability to address complex business challenges using advanced Google Cloud technologies. Among his notable achievements, Andranik's proudest project involved overcoming significant obstacles to deliver a solution that had a substantial impact in its application area.
Main expertise
- Computer Vision 6 years
- Data Engineering 4 years
- OpenCV 6 years
Other skills
- Kubeflow 3 years
- Kubernetes 3 years
- ChatGPT API 2 years
Selected experience
Employment
Machine Learning Engineer (MLOps)
Sportion AM - 3 years 9 months
- Conducts research to identify suitable machine learning algorithms and tools for specific applications.
- Designs, builds and deploys machine learning models tailored to address diverse business challenges.
- Utilizes Google Cloud technologies to develop innovative solutions and enhance the efficiency of machine learning projects.
- Applies in-depth knowledge of established machine learning models and techniques to create effective and reliable solutions for various industry problems.
Technologies:
- Technologies:
- Data Engineering
Kubeflow
- MLOps
Machine Learning
Python
NumPy
Pandas
Scikit-learn
Google Cloud
Research Scientist
DataFoundry - 2 years
- Deploys, monitors, and tests machine learning models, ensuring their seamless integration into operational systems.
- Develops APIs for machine learning models, enabling efficient communication and utilization of the models in diverse applications.
- Specializes in real-time drug name misspelling generation, Twitter scraping, and sentiment analysis, leveraging expertise in Python, JSON, web scraping, and natural language processing (NLP).
- Led the development of a health-related semantic classification system using text distance metrics, Python, and JSON, allowing for accurate identification of potential risks associated with specific medications by analyzing adverse drug effect tweets. This solution is valuable for pharmacovigilance and drug safety monitoring.
- Participated in a Kaggle competition and developed an API for heart disease classification using Python and Flask.
- Trained machine learning models to classify heart disease based on medical parameters, offering healthcare professionals a quick and reliable tool for assessing the likelihood of heart disease in patients.
Technologies:
- Technologies:
-
Python
-
NumPy
-
Pandas
-
Scikit-learn
TensorFlow
Data Expert - Software Engineer
cognaize - 6 months
- Collaborates on the development of internal management tools using Python, focusing on API development for seamless functionality.
- Proficiently manipulates Excel/CSV, PDF, and JSON files, demonstrating expertise in document engineering using Python scripting.
- Contributes to enhancing data processing and management workflows through effective file manipulation techniques.
- Ensures accuracy and efficiency in file handling processes, enabling streamlined data operations within the organization.
Technologies:
- Technologies:
-
Python
-
NumPy
-
Pandas
Education
MSc.Bioinformatics
Yerevan State University · 2016 - 2018
BSc.Bioinformatics
Yerevan State University · 2012 - 2016
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