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ANDERS KISS

+1-754-***-****

adyfzp@r.postjobfree.com

** ****** **** **********, ** 01719 U.S.A.

https://www.linkedin.com/in/anders-kiss-92740a25/

www.github.com/anderche

https://public.tableau.com/profile/anders#!

PROFILE

A Data Scientist most interested in machine learning, data analysis, and data visualizations that make sense from big data and drive strategic decisions. I have a Master of Science in Artificial Intelligence and a Master of Science in Biomedical Technology Development & Management with technical skills in Python, Power BI, Tableau, SQL, Natural Language Processing (NLP), time-series data, quantitative modeling, computer vision, and fullstack app development (Django), and version control with Git / GitHub. Specializations include machine learning, deep learning (e.g. Keras and Tensorflow libraries), Convolutional Neural Networks (CNN) deep learning models, feature engineering, feature selection, hyperparameter tuning, and recommendation systems. For my dissertation (MSc. in AI) I utilized Python’s Keras and Tensorflow libraries for a comparison study of two recurrent neural network algorithms - Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU) - of time-series data as well as a feature analysis of commodities, currencies, and economic data in order to predict the future price of a financial asset: https://anders-kiss.gitbook.io/modeling-digital-assets-with-deep-learning/ SKILLS

AWS, Azure, Databricks, Django, Docker, Excel, Flask, Git/GitHub, Google Cloud Platform, HTML5,

JavaScript, JSON, Keras, Matplotlib, MLflow, MySQL, Neo4j, NumPy, Pandas, Postgres, Power BI, Project

Management, PySpark, Python, PyTorch, R,

RapidMiner, React.js, Ruby on Rails, SageMaker,

Scikit-Learn, Seaborn, Snowflake, SQL, Tableau,

Tensorflow

EMPLOYMENT

Data Scientist 10/2022 to Present

Gemological Institute of America (GIA) – remote

- Applied neural networks for time-series datasets (instrumentation failure predictions) with various algorithms: Long Short-Term Memory (LSTM’s), Gated Recurrent Unit (GRU’s), Transformers, Support Vector Regression (SVR’s), Temporal Convolutional Networks (TCN’s), and Echo State Networks

(ESN’s).

- Applied Simple Exponential Smoothing (SES) and Holt's Linear Exponential Smoothing to analyze time-series data to predict when instrument-failure might occur based on historical data, and ARIMA based on previous failures / autocorrelation.

- Developed deep learning and machine learning models for diamond grading purposes based on computer vision and image classification algorithms using Python.

- Applied cloud-based platforms (e.g., AWS Sagemaker, AWS S3, MLFlow) for deployment of scalable machine learning models.

- Presented management with findings (feature engineering, algorithm comparison, model architecture and results).

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Medical Device Consultant 11/2020 to 09/2021

Varian – remote

- Managed the international registration of medical devices (oncological, embolization nanoparticles) using Python to monitor and track requirements, and to consolidate country-specific requirements

(including Supply Chain, Engineering, Safety/Complaint data, and Marketing product documentation)

- Implemented a Python-based web scraper to gather relevant regulatory updates from international medical device registration bodies, ensuring the team was updated in real time.

- Licensed the nanoparticles in the European Union (CE-Mark registration) collaborating alongside Engineering, Operations, Marketing, Product Management, and Sales departments. Medical Device Consultant 09/2019 to 03/2020

Medtronic – remote

- Revised software upgrade changes for new government submission using Python to automate the review of code changes and check for compliance with regulatory requirements.

- Submitted European Medical Device Regulation (MDR) and technical file (CE-Mark) dossiers for nerve-monitoring spinal product.

- Provided regulatory support in New Product Development meetings pertaining to IEC 60601-1 Basic Safety and Essential Performance, IEC 60601-1-2 EMC, IEC 62366 Usability, IEC 62304 Software deliverables.

Regulatory Affairs Specialist 02/2017 to 09/2018

Johnson & Johnson – Irvine, California, U.S.A

- Worked with Chinese regulators and engineers to register product lines with the Chinese health agency (CFDA)

- Submitted 30x registrations for Europe, China, Japan, Russia, and Brazil for entire product lines

- Drafted European Technical Files for Sterilizers and Disinfection capital equipment

- Worked with Engineering, Marketing, Quality, and Operations to finalize registration deliverables EDUCATION

Master of Science, Artificial Intelligence 09/2021 to 09/2022 Dublin Business School - Dublin, Ireland

Coursework

o Machine Learning & Pattern Recognition, Deep Learning, Reinforcement Learning, Recommender Systems, Natural Language Processing (NLP), Programming for Data Analysis, Graph Theory, Cognitive & Ethical Dimensions of Artificial Intelligence

Dissertation

o A comparison study of LSTM and GRU algorithms and a feature analysis of multivariate macroeconomic features pertaining to their capacity to improve accuracy of Bitcoin price predictions. https://anders-kiss.gitbook.io/modeling- digital-assets-with-deep-learning/

Projects

o A data acquisition / preprocessing pipeline script to obtain stock market data, create technical indicator, with data persisting to a database (Microsoft SQL Server). https://github.com/Anderche/data-acquisition-and-preprocessing- pipeline

o A Content-based recommender system (RS) script is for a content-based recommender system (RS) that I built. This basic system recommends an Airbnb listing to a User based on the description fields of a their historical stays. The code implementation compares recommendation accuracy of the BERT and TF-IDF algorithms. https://github.com/Anderche/content-based-recommendation-system o An NLP topic modeling application to better understand the major themes for that day’s news headlines by ingesting the Python API, NewsAPI. It can be found here: https://github.com/Anderche/Natural-Language-Processing_Topic- Modeling

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A Python script that utilizes that targets communities from the MovieLens database (containing ~38,000 movies) via the graph theory (machine learning) algorithms, Label Propagation (Community Detection Algorithm), and K-Nearest Neighbors (Similarity Algorithm). https://github.com/Anderche/graph-theory-profitable-movie-ideas o A Tensorflow / Keras image classification model compared the accuracy of three image classification models: ResNet50, VGG16, and a custom deep learning, neural network. For each model above, first a baseline model was trained and evaluated. Afterwards, a dropout layer was added to each model and compared in terms of the baseline models. https://github.com/Anderche/image_classification Data Analytics Bootcamp 08/2020 to 10/2020

WeCloudData Online - online - https://www.wedlouddata.com

- Power BI, Tableau, SQL, Python (financial analysis, web scraping), Marketing Analytics, Digital Analytics, Supply Chain Analytics, Healthcare Analytics, Business Analytics Fullstack Web Development Program 01/2019 to 03/2019 Le Wagon - Milan, Italy - https://www.lewagon.org

- Ruby on Rails, React.js, HTML5, CSS3, JavaScript, Flexbox, CSS Grid, jQuery, Authentication & Authorization mechanisms, Geocoding (MapBox), Search (Algolia), UX/UI design Master of Science, Biomedical Technology Development & Mgmt. 08/2009 to 05/2011 Georgetown University - Washington, D.C., U.S.A.

- Bioinformatics, Biomaterials, Project Management, Immunology, Pharmacology, Molecular Biotechnology, Preclinical Product Evaluation, Design & Conduct of Clinical Trials, Product Leadership, Legal & IP Issues, Commercial Development, Leadership & Innovation in a Tech Environment Bachelor of Science, Biological Sciences 08/2005 to 05/2009 Virginia Polytechnic Institute & State University - Blacksburg, Virginia, U.S.A. PROJECTS

ZAETAE, Inc.

Startup Chile accelerator to (Santiago, Chile) 10/2015 to 01/2017

- I created a marketplace to help patients find healthcare providers with surgical robotic and Artificial Intelligence-based software diagnostics; awarded a $30,000 USD grant from Startup Chile

(www.startupchile.org)

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