Data Analytics Research Associate

John Mariano

** ******* **

Westford, MA *****

978-***-****

****.*****.*******@*****.***

EXPERIENCE

Biobot Analytics, Cambridge, MA — Research Associate II Dec 2022 - Sep 2023

Performed RNA extraction and sequencing preparation for viral samples. Processed and managed large datasets to support public health monitoring of SARS-CoV-2 Nationwide.

Collaborated with cross-functional teams to design and improve data processes.

UMass Memorial Medical Center, Worcester, MA —

Research Associate I

Oct 2021 - Dec 2022

Generated high-quality NGS libraries and maintained metadata integrity for downstream SARS-CoV-2 genomic surveillance

Performed NGS library preparation, as well as RNA extraction, quantification, and quality control for Illumina-based sequencing workflows.

Prepared and handled single-cell suspensions and PBMCs for downstream applications.

EDUCATION

University of Massachusetts, Lowell — Master of Science, Bioinformatics

2023 - 2024 GPA: 3.960

University of Massachusetts, Amherst — Bachelor of Science, Biology

2017 - 2021 GPA: 3.775

PROJECTS

Chest X-ray Classification Using CNNs — Python

Developed and optimized convolutional neural networks using TensorFlow to classify pleural effusions in chest X-rays. Processed and SUMMARY

Bioinformatics specialist with

nearly 3 years of experience in

public health research and omics

data workflows. Skilled in R,

Python, and SQL, with a growing

focus on proteomics data

processing, data curation, and

building user-friendly

visualization tools to support

translational research and target

discovery.

SKILLS

Sequencing (NextSeq200), NGS,

Data Visualization, Omics Data

Processing, Bioinformatics

Pipeline Development, Python,

R, Bash, SQL (MySQL), SAS,

DNA/RNA Isolation/Extraction,

RNA to cDNA, NGS Library Prep,

PCR, PBMCs, Single Cell

Suspension

TOOLS & ENVIRONMENTS

Git, Galaxy, Jupyter, VS Code,

Linux/Unix

augmented large image datasets to improve model accuracy. Conducted testing and debugging to ensure algorithm efficiency and reliability. Glioblastoma Pathway Analysis — Python

Applied statistical methods to analyze transcriptomic and genomic data. Identified key mutations in IDH1 pathways and their clinical significance. Leveraged Python for data structuring and exploratory analysis. Predictive Modeling for Health Data — SAS

Designed logistic regression models to analyze demographic factors and health outcomes using SAS. Developed interpretable visualizations to communicate key findings. Documented processes for reproducibility and knowledge sharing.

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