Oana Strut

Skills

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Frameworks: Tensorflow, Keras, scikit-learn, SciPy, MXNet

Data manipulation: Pandas, Numpy, Nltk

Data visualization: Folium, Matplotlib, Seaborn, Plotly, ggplot, Bokeh, Dash

Image processing: OpenCV, scikit-image

Web crawling: Beautiful Soup

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Tools:

IDEs: Visual Studio Code, JupyterLab, PyCharm

Cloud: AWS, Azure, Google Cloud

Data and machine learning platforms: Dataiku, Neo4j

Model training and evaluation: Tensorboard, MLFlow

Model deployment: Flask API, Docker

Virtual environments: Anaconda, Python environments

Version control systems: Git

Issue tracking: Jira

Languages: Python, R, SQL

Platforms: Windows, Linux

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Work Experience

Machine Learning Engineer, Cognizant Softvision, 2019 - present

Main projects:

- Hybrid recommender system for trader matching on bond market area. Based on a single or a list of bonds the user wants to sell or buy, return top traders who might be interested in them.

- Automation of trading sessions generated by admins to see on which bonds would be better to generate swarms and at what price.

- Virtual try-on app for a lipstick brand that thanks to its artificial intelligence-based facial recognition, landmarks detection, virtual and augmented reality technology lets you virtually try on any color of lipstick and see how the shade will look on your lips.

- Demand forecasting system based on different metrics related to demand but also on different third-party data to see how factors like weather or economicalindicators will affect sales in the future.

Tools: Python, Visual Studio Code, JupyterLab, PyCharm, AWS, Azure, Google Cloud, Dataiku, Neo4j, Flask API, Git, Jira.

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Senior Data Scientist, Evalueserve, 2018 - 2019

Main projects:

- Provide technical support to create solutions that can be integrated into sales campaigns.

- Provide time series forecasting models to predict sales values on short, medium and long term.

- Develop real-time dashboards on multiple data sources (Azure, SQL Server, Access, SharePoint) to monitor the activity of different operational KPIs in the
water treatment area.

- Develop dynamic dashboards in Power BI with personalized content capabilities for sales optimization purposes to modelling the outcome of
specific hiring, firing and client/team re-allocation decisions.
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Frameworks: Scikit-Learn, Keras, Tensorflow, XGBoost, Folium, Beautiful Soup, Pandas, Matplotlib, Seaborn, Plotly, Scipy.

Technologies: Python, PyCharm, R Studio, Azure, Power BI Desktop, Power BI Pro, SQL Server.

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Data Scientist, null, 2016 - 2018

Main projects:

- Machine condition monitoring and fault detection to predict and prevent failures, production breakdowns in operations, detect early warning signs and
reduce unnecessary downtime.

- Provide advanced analytics methodologies in the area of maintenance planning for different rotating machines to improve the operational efficiency, including identify the reasons behind wear cases and estimate the possible future alarms by finding specific patterns and potential anomalies in data.

- Enhancing customer behavior analysis by analyzing open-ended survey responses and extracting opinions, emotions and sentiments in unstructured text data.

- Benchmarking efficiency of different entities to identify the best performing units and provide actionable measures for performance improvement.

Technologies:

R Studio, R Shiny, Power BI Desktop, SQL Server.

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Junior Associate, Romanian Economic Institute, 2015 - 2016

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Main project:

- Analyze the ability of clinics to enter the medical tourism market using machine learning models.