Vaishnavi Nalla
Data Analyst @Merck
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WORK HISTORY
Data Analyst @Merck
VA, US
Collaborated with bioinformatics and research teams to define analytics requirements and KPIs for predicting high potential drug candidates, reducing early-stage target selection time by 25%. • Extracted, consolidated, and stored large-scale datasets (~5M+ records) from genomic, proteomic, and chemical compound sources using SQL, Python (pandas, NumPy), and AWS S3, ensuring 99.8% data accuracy and scalable access for modelling. • Cleaned and transformed experimental data by handling missing values, standardizing compound identifiers, and scaling features in Python, improving dataset quality and reducing predictive errors by 30%. • Performed exploratory data analysis using Python (Seaborn, Matplotlib) and Tableau to identify key biomarker compound correlations and trends that guided molecule prioritization. • Prepared and validated datasets for AI/ML modeling, supporting Random Forest and XGBoost algorithms, contributing to a 15% increase in prediction accuracy for candidate molecules. • Developed Tableau dashboards visualizing compound efficacy scores, predicted activity, and trends, enabling real-time, data-driven decision-making for research teams. • Automated weekly data ingestion, transformation, and loading using Python ETL scripts, reducing manual preparation time by 40% and ensuring reproducible analytics pipelines. • Documented datasets, pre-processing steps, and dashboard outputs in alignment with SDLC standards; presented findings to stakeholders to support regulatory compliance and research transparency.
EDUCATION
Sree Chaitanya Institute of Technological Sciences
BTech - Bachelor of Technology
University of Bridgeport
Master of Science - MS
ABOUT VAISHNAVI NALLA
I’m a Data Analyst with 3+ years of experience in the SaaS and pharmaceutical industries, passionate about turning complex data into meaningful insights that drive smarter decisions. I specialize in data modeling, statistical analysis, and dashboard development, with hands-on expertise in Python, SQL, Tableau, and AWS.At Merck, I worked on automating clinical trial reporting and improving patient data accuracy, helping reduce delays and enhance trial outcomes. At Druva, I developed customer health scoring models that improved retention strategy and reduced churn through predictive analytics and machine learning.With a Master’s in Computer Science from the University of Bridgeport, I bring both technical depth and business understanding to the table. I enjoy collaborating across teams in Agile settings, and I’m always eager to learn, optimize, and innovate using data.
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