Marketing Analytics Data Analyst

SUMMARY: Data and marketing analytics professional with 5 years of experience in deploying cloud-native architectures for AI-driven applications, integrating AWS and Azure services to automate workflows and scale data processing. Expertise in NLP, semantic modeling, and real-time analytics across recruitment and marketing domains.

SKILLS:

Programming: Python, SQL

Databases: MySQL, MS SQL Server, PostgreSQL, Azure SQL Database, Google BigQuery

Data Engineering & ETL: Azure Data Factory, SSIS

Data Visualization: Power BI, Plotly, Matplotlib

ML/AI: Scikit-learn, TensorFlow, Keras, NLP (NLTK, Spacy), OpenAI (GPT-3.5/4)

Cloud & DevOps: AWS (S3, SNS, SQS, EC2, ECR, Lambda, Step Function, EventBridge), Azure (Blob Storage, AI Search), Docker

Tools: Git, JIRA, Figma, Excel, LocalStack, Google Analytics

PROFESSIONAL EXPERIENCE:

HireUp, Inc., Wilmington, DE, USA (ML Engineer, Part-time Volunteering Contributor) April 2025-Present

Architected and deployed a scalable, event-driven cloud architecture for automated resume processing and skill assessment, leveraging AWS services (Lambda, Step Functions, EventBridge, S3, SNS, SQS) and LocalStack for local testing, enabling real-time insights and reducing manual effort by 80%.

Developed robust ML workflows leveraging AWS Bedrock and Textract for NLP-based resume parsing, anonymizing, scoring, and verification, integrating AI detection, plagiarism analysis, and behavioral insights to ensure assessment integrity, increasing accuracy by 90% and enhancing candidate evaluation credibility.

Agile Datapro, Inc., Campbell, CA, USA (Data Analyst, Remote) Aug 2024-Present

Developed a GenAI-powered resume recommendation system using Azure OpenAI GPT-3.5 Turbo to interpret recruiter prompts and rank resumes from structured JSON datasets in Azure Blob Storage. Integrated with Flask APIs to reduce response time by 50% (from ~5s to under 2.5s), replacing manual filtering with dynamic scoring and candidate insights.

Designed and deployed hybrid ETL pipelines using Azure Data Factory and Python scripts, integrating OpenAI GPT-3.5-turbo to extract structured candidate data from unstructured resumes. Generated JSON and CSV outputs for easy rendering, filtering, and downstream scoring, reducing resume processing time by 40% and enabling scalable storage in Azure Blob and Azure SQL.

Developed an interactive Flask/React.js-based chatbot interface providing recruiters with real-time candidate insights (match scores, skills alignment), dynamically rendered resumes and cover letters (HTML/PDF), streamlining recruiter workflows and accelerating hiring decision cycles by 30%, validated through internal performance tracking metrics.

Accenture Solutions Private Limited (Data Analyst) Aug 2018-July 2021

Built automated ETL pipelines using SSIS to integrate and transform sales and web data (Google Analytics, social media API) into Google BigQuery, reducing data load times by 50% and enabling marketing teams to generate insights 30% faster.

Analyzed website traffic and customer behavior data through SQL (SSMS, BigQuery) and conducted A/B tests comparing personalized and generic recommendations, achieving an 8% absolute increase in Conversion Rate (CVR); statistically validated results via hypothesis testing (SciPy, Statsmodels).

Developed customer lifetime value (CLV) models using Python (BG/NBD, Gamma-Gamma) to segment customers and refine targeted marketing strategies, increasing customer retention effectiveness by 10%, measured by repeat purchase rates.

Persistent Systems Limited (Marketing Data Analyst) July 2017-July 2018

Optimized complex SQL queries (recursive CTEs), reducing customer database query time by 30%, expediting strategic marketing decisions.

Enhanced customer outreach effectiveness by 40%, leveraging data cleansing (SQL/Excel) for accurate targeting in e-commerce marketing campaigns.

Developed Power BI dashboards visualizing critical KPIs (Total Revenue, Average Order Value), accelerating report generation speed by 100%, and enhancing data-driven decision-making across 5 marketing teams.

PROJECTS:

Trend Prediction and Probabilistic Modeling of Live News Data using Neural Networks [Link] Apr 2023

Built an automated real-time web scraping pipeline using Python (Scrapy, Selenium) to extract and preprocess live news text data, reducing data collection and cleaning time by 65% compared to previous manual methods.

Implemented NLP-driven analysis, combining sentiment evaluation (VADER, TextBlob) and topic modelling (LDA), accurately categorizing news articles into global themes with 72% prediction accuracy validated on unseen data.

Developed a neural network-based trend prediction model (MLP Classifier), iteratively tuned hyperparameters to achieve 87% classification accuracy, and visualized actionable insights through interactive geographic dashboards built in Power BI.

EDUCATION:

Northeastern University, Boston, USA Master of Science in Information Systems [Link]

Pune University, Pune, India Master of Business Administration in Marketing and HR [Link]

COEP Technological University, Pune, India Bachelor of Technology in Mechanical Engineering [Link]

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