Data Analyst - SQL, Python, Tableau, ML Modeling expertise

Pallavi Ramineni

Data Analyst

Jersey City, NJ h.ps://www.linkedin.com/in/pallavi-rm-/ 551-***-**** ******************@*****.*** Data Analyst with 3+ years of experience in data analysis, repor/ng, and visualiza/on across financial services and technology. Proficient in SQL, Python, R, Tableau, Power BI, and skilled in machine learning, predic/ve modeling, and applied mathema/cs to uncover trends and drive insights. Adept at data cleaning, ETL processes, and dashboard development, with a proven ability to translate complex data into business strategies that improve efficiency, reporOng accuracy, and decision-making. WORK EXPERIENCE

Vosyn

Data Engineer /ML Jan 2025 – Present

• Designed and deployed scalable data extraction and cleaning pipelines using containerized microservices to enhance reliability and reusability.

• Implemented end-to-end CI/CD/CT pipelines with Kubeflow on Kubernetes and Vertex AI, reducing model deployment time by 70% and streamlining MLOps workflows.

• Built and optimized inference pipelines on Google Cloud Platform (GCP) with auto-scaling capabilities, ensuring high- performance and cost-efficient model serving for production workloads.

• Collaborated with product, UX, and data teams to identify bottlenecks, drive process improvements, and enhance data pipeline efficiency and user experience.

SkyIt Services

R&D Data Analyst Aug 2024 – Dec 2024

● Partnered with business stakeholders to gather requirements and translate them into technical specificaOons, ensuring accurate coding and data mapping (SQL, ETL) for enterprise projects.

● Conducted in-depth data analysis (SQL, Excel, Tableau) to support system enhancements and communicated findings to operaOng and development teams, reducing requirement gaps by 20%.

● Collaborated with upstream data providers and downstream applicaOon teams to resolve data integraOon and workflow issues, improving data accuracy and system reliability.

● Delivered analysis results through dashboards and presentaOons (Tableau, Power BI, Excel), enabling leadership to make informed business and technical decisions.

● Performed impact analysis on upstream data changes and user requests, minimizing risks and avoiding project delays.

● Developed and executed User Acceptance TesOng (UAT) scripts, coordinaOng with end users to validate system funcOonality and ensure smooth deployments.

Saint Peter’s University

Graduate Research Assistant Nov 2023 – Nov 2024

• Performed advanced data analysis on MIMIC-III healthcare datasets using Python (Pandas, NumPy, Scikit-learn) and SQL, idenOfying key clinical risk factors that improved diagnosOc accuracy by 15%.

• Developed and automated interacOve dashboards in Power BI, integraOng data from Azure SQL Database, reducing manual reporOng Ome by 40%, and enabling real-Ome clinical decision-making.

• Engineered end-to-end ETL pipelines using Azure Data Factory and Databricks, implemenOng data cleaning, transformaOon, and validaOon workflows to deliver real-Ome analyOcs for healthcare professionals.

• Led a cross-funcOonal 3-member R&D team to design and deploy real-Ome word cloud visualizaOons using Natural Language Processing (NLP) techniques for U.S. news analysis.

• Integrated RESTful APIs for automated data ingesOon and model updates, ensuring scalable, dynamic text analyOcs pipelines with minimal latency.

• Designed and deployed interacOve data visualizaOon features using Python (Plotly, Dash) and Figma prototypes, improving user engagement and accessibility for publicaOon dashboards.

• Presented analyOcal findings and research outcomes to technical and non-technical stakeholders, influencing data-driven policy decisions and advancing AI-driven R&D iniOaOves in healthcare and informaOon systems. LTIMindtree

Mean Full Stack Developer Jan 2022 - Jul 2023

• Designed and developed rapid prototype applications to test emerging technologies and validate R&D concepts.

• Built a Digital Restaurant Web App using Angular, Node.js, Express.js, and MongoDB, enabling local eateries to expand digital reach.

• Developed and tested software releases, ensuring stability and performance through structured QA and validation

• Implemented secure authentication, API testing (Postman), and backend optimization, improving reliability and data integrity.

• Collaborated with cross-functional teams to analyse performance data, resolve issues, and drive continuous improvement in system design.

EDUCATION

Saint Peter’s University USA

Master of Science - Data Science Sep 2023 – May 2025 Sreenivasa insOtute of technology and management studies India Bachelor of Engineering: Computer science engineering May 2018 – Jun 2022 SKILLS & INTERESTS

Data Analysis & Visualiza/on: SQL, Tableau, Power BI, Excel (Pivot Tables, VLOOKUP, Macros), Python (Pandas, NumPy, Matplotlib, Scikit-learn), R

Database & ETL Tools: Oracle SQL, MS SQL Server, PostgreSQL, MySQL, Tableau Prep, Alteryx, SSIS Machine Learning & Sta/s/cs: Regression Analysis, ClassificaOon, Clustering, PredicOve Modeling, Time Series ForecasOng, Feature Engineering, Model EvaluaOon, Hypothesis TesOng

Mathema/cs & Quan/ta/ve Methods: Linear Algebra, Probability, StaOsOcs, Calculus, OpOmizaOon, StaOsOcal Inference, Data Modeling Project & Repor/ng: Dashboard Development, Data Modeling, KPI Tracking, Data ValidaOon, Data Quality Assurance, ForecasOng, Ad-hoc ReporOng

Methodologies & Techniques: Data Cleansing, Data Mapping, Impact Analysis, UAT (User Acceptance TesOng), Requirements Gathering, Root Cause Analysis, Process Improvement

Collabora/on & Tools: JIRA, Confluence, MS Excel, MS PowerPoint, MS Project, SharePoint, Git PROJECTS

Stock Market Forecas/ng Dashboard (Python, NLP, Power BI)

● Analyzed historical stock trends and social media senOment using NLP, idenOfying key pa.erns influencing stock performance.

● Built a Power BI dashboard for traders to visualize senOment shims in real Ome, improving decision-making efficiency.

● Reduced predicOon error by 18%, enabling more accurate investment strategies. F1 Data Engineering Pipeline – (Azure, Databricks, Delta Lake, Data Factory, Power BI)

• Data Pipeline & IngesOon: Built Azure Data Lake with Raw, Processing, and PresentaOon layers; ingested JSON/CSV data from Ergast API into Databricks using Key Vault for secure access.

• TransformaOon & Loading: Cleaned and opOmized data with Spark; converted to Delta Lake with incremental loading to prevent duplicates and enable versioning/Ome travel.

• OrchestraOon & VisualizaOon: Managed automated pipelines with Azure Data Factory; developed interacOve Power BI dashboards for driver standings, constructor standings, and race results. CERTIFICATION

● Cer/fied in Big Data Analy/cs course

● Cer/fied in Python for Data Science and Machine Learning course

● Cer/fied in Genera/ve AI for beginners

● Cer/fied in Prompt Engineering in ChatGPT

● Cer/fied from Accenture on Ar/ficial Intelligence

● Cer/fied from Coursera on project management.

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