About

Mark Chesney is a Senior Associate Data Engineer at dentsu media with over 4 years of relevant experience in data wrangling, modeling, analysis, and visuals. He believes that data can be a valuable asset and not a burden or a threat, and data technology done right can unite us rather than divide us. Mark is passionate about combining his data intuition, passion for learning, analytical skills, and programming to continue helping clients make sense of data. He has experience in machine learning research, SQL databases, and cloud computing in Amazon Web Services (AWS). Mark's GIS projects include impact evaluation in vegetative restoration maps (NDVI), and georeferencing Earth at Night imagery for data modeling. Machine learning projects include PCA (dimensionality reduction) and Clustering on marketing analytics dataset, and Transfer Learning for Feed-Forward Neural Network Classifier. He has also worked on data engineering and cloud computing projects, including NoSQL Data Warehouses in Redshift, Data Lakes in Spark/PySpark on Elastic Map Reduce (EMR) clusters and Simple Storage Service (S3) buckets. For data pipelines and DAGs, Apache Airflow. Lab projects include core Amazon web services such as Elastic Cloud Compute (EC2), Elastic Block Storage (EBS), and Relational Database Service (RDS). Mark holds a Master's Degree in International Affairs, focused on International Economics, and a Graduate School Certificate in Computer Science. He is certified in Java and Python programming and as an MS Excel Expert. He is proficient in developer tools that include SQL, Python, R, Java, and C++. He is experienced in Jupyter Notebooks, including Pandas, NumPy, SciPy, and scikit-learn; machine learning in Keras and PyTorch; Visualization using Matplotlib, Plotly, Seaborn, and Tableau Public. He is also proficient in Salesforce Lightning CRM. In his past roles, Mark has worked as a Data Engineer at cbts and as a Data Engineer (Co-op), Digital Therapeutics at Novo Nordisk. At cbts, he supported the extraction & transformation of data objects between systems across the enterprise. At Novo Nordisk, he developed an in-house Python package application, using AWS S3 and Redshift, empowering the Data Scientists with direct self-service data lake access.