John J
Chicago,IL
Summary
Meticulous Analytics Engineer eager to provide holistic data acquisition and management services. Leverages novel techniques and technologies to squeeze maximum value from owned and acquired assets. Dedicated to exceeding business goals through careful exploitation of all available resources.
Overview
9
9
years of professional experience
Work History
Pipeline Data Analytics Engineer
DDDD
08.2019 - Current
- Drafted technical documentation for internal business areas and processes, incorporating factors such as technical design, data manipulation, ETL and storage management.
- Tracked and leveraged data trends, aggregate statistics and volume fluctuations to hone [Type] performance metrics.
- Collaborated with internal and external stakeholders to optimize data sourcing pipelines and verify data quality.
- Determined data storage and optimization policies, shaping organization efforts to enhance performance.
Pipeline Data Analytics Engineer
STSTST
08.2018 - 07.2019
- Optimized data sources and processing rules to enhance data quality through design and development phases.
- Deployed predictive analytics models to forecast future trends.
- Analyzed data to identify root causes of problems and recommend corrective actions.
- Created dashboards to monitor and track key performance indicators.
- Implemented business intelligence solutions to increase operational efficiency.
Data Scientist
RC
05.2014 - 08.2014
- Built company A/B testing frameworks to test model quality.
- Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling.
- Set up SQL database on cloud servers to store client data for query analysis.
- Applied statistical and algebraic techniques to interpret key points from gathered data.
- Discovered stories told by data to present information to scientists and business managers.
Education
Master of Science - Data Science
GofT
12.2024
Bachelor of Science - Chemical Engineering
UofC
04.2017
Skills
- LANGUAGES: Python, R, C
- CLOUD/DATABASE: Azure, AWS, MySQL, Apache Spark
- SUPERVISED ML: Linear and Logistic regression, Random Forest, K-Nearest Neighbors, Bayesian Networks, Support Vector Machines (SVM)
- UNSUPERVISED ML: Anomaly Detection, Clustering, Dimensionality Reduction (PCA, ISOMAP)
- WEB SCRAPING: BeautifulSoup, REST APIs, Selenium
- DATA VISUALIZATION: PowerBI, Tableau, Matplotlib/Seaborn
Websites
Projects, as a part of Udacity Data Analyst Program
· Exploring Weather Trends: [SQL, Python] Analyze, Compare local and global temperature trends
· Bike Sharing Demand Prediction: [Python] Utilized random forest to predict bike sharing demand in Washington DC.
· Subway Ridership Prediction: [Python] Analyzed & used linear regression to predict New York, Washington, and Chicago Subway ridership.
· Wrangle OpenStreetMap Data: [SQL] Improved the data quality of Birmingham with data wrangling and stored clean data in SQL for query and exploration.
· P2P Lending Exploratory Data Analysis: [R] Explored multiple variables for distributions, outliers, and anomalies.
Timeline
Pipeline Data Analytics Engineer
DDDD
08.2019 - Current
Pipeline Data Analytics Engineer
STSTST
08.2018 - 07.2019
Data Scientist
RC
05.2014 - 08.2014
Master of Science - Data Science
GofT
Bachelor of Science - Chemical Engineering
UofC
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