Hello, I'm

Ayush Patel

Data Analyst

Data Analyst with 3+ years of experience at OpenText, Concordia University, and Tech Mahindra. I specialize in SQL, Python, ETL pipelines, predictive modelling, and cloud platforms — turning complex data into measurable business outcomes.

About Me

I'm a Data Analyst with 3+ years of professional experience working across the full data lifecycle — from building ETL pipelines and transforming large-scale datasets, to developing predictive models and delivering dashboards that drive real business decisions.

Currently at OpenText in Toronto, I've built customer churn models that improved retention by 22%, processed 10M+ records using SQL and Python, and reduced manual reporting effort by 50%. My background spans enterprise analytics, cloud platforms (Azure, Snowflake, BigQuery), and machine learning using Scikit-learn.

I hold a Master's in Applied Computer Science from Concordia University with a focus on Data Analytics and AI, and I'm certified in Power BI (PL-300) and Azure Fundamentals (AZ-900).

Education

Master's in Applied Computer Science

Concordia University

Canada

2023 - 2025

Bachelor's in Computer Science

Gujarat Technological University

India

2019 - 2023

Skills & Technologies

Programming Languages

PythonSQLRDAX

Data Visualization & BI

Power BITableauMatplotlibSeabornPlotlyExcel

Machine Learning & AI

TensorFlowCNNOpenCVLangChainNLPScikit-learn

Databases & Data Modeling

PostgreSQLMySQLSnowflakeMongoDBCassandraOracleRDBMSSchema DesignQuery Optimization

ETL & Data Processing

PandasNumPyData CleaningETL PipelinesData WranglingAzure Data FactoryAirflowPySparkdbt

Tools & Frameworks

JupyterGitVS Coden8nZapierConfluenceJIRAServiceNow

Cloud Platforms

Microsoft AzureAzure Data FactoryAWS BasicsSnowflakeBigQueryDatabricksGCP

Statistical Analysis

Regression AnalysisHypothesis TestingA/B TestingDescriptive StatisticsKPI Analysis

Projects

Adaptive Multi-Agent Chatbot System

Engineered a modular multi-agent system with specialized agents (General, AI, and Admissions) using dynamic routing to assign queries based on context. Implemented Q-learning algorithm that optimizes response parameters (temperature, top-p, max tokens) in real-time based on user feedback. Integrated LangChain's ConversationBufferMemory for multi-turn dialogue and FAISS vector store for past interaction retrieval. Augmented responses with Wikipedia API integration for factual data. Features a self-correcting feedback loop that penalizes generic answers and rewards high-quality outputs.

PythonOllamaLangChainFastAPIFAISSMistral

Bank Loan Performance Analysis

Developed a comprehensive suite of 3 dashboards (Summary, Overview, Details) tracking loan portfolio performance for a major financial institution. Engineered complex SQL queries and Power BI DAX measures for real-time KPI monitoring. Achieved clear visibility into 'Good' vs 'Bad' loan segmentation by DTI ratios, interest rates, and employment length. Implemented geospatial mapping and monthly trend forecasting to identify high-growth lending regions.

Total Applications

38.6K

Funded Amount

$435.8M

Avg Interest Rate

12.0%

Avg DTI

13.3%

SQLPower BIExcelData ModelingDAX

Facial Expression Recognition

Developed a Convolutional Neural Network (CNN) to classify facial images into four emotional categories: Angry, Neutral, Bored, and Focused. Combined FER2013 dataset with 1,500+ scraped images. Implemented HAAR classifiers for face detection and Unsharp Masking for image enhancement. Achieved 70% accuracy using Adam optimizer with early stopping across 100 epochs.

PythonCNNOpenCVMatplotlibTensorFlow

Warzone: Multi-Agent Strategy Game Engine

Built a 10,000+ line-of-code game engine in Java utilizing MVC pattern and SOLID principles for modularity. Engineered 4 distinct AI player modes (Aggressive, Benevolent, Random, Cheater) using the Strategy Pattern. Achieved high system stability through JUnit 5 testing suites with automated tournament modes and map validation logic. Integrated Java Serialization for state management and a custom Map Editor for .map file parsing.

System Architecture

ControllerModelViewStrategyObserverBuilder
JavaMavenJUnit 5Java SwingDesign Patterns

Professional Experience

A track record of delivering impactful data solutions across academic and industry settings.

Industry

Data Analyst

OpenText

September 2025 – Present
Toronto, ON, Canada
  • Performed large-scale data profiling and trend analysis across multiple systems, helping uncover anomalies and process gaps that contributed to a 22% improvement in reporting reliability.
  • Analyzed and transformed 10M+ records using SQL and Python, improving data accuracy and enabling faster business reporting across multiple operational and analytical workflows.
  • Reduced manual data extraction and preparation effort by 50% through the creation of reusable SQL scripts, standardized logic, and automated reporting-ready data layers.
  • Developed advanced predictive models using Python (Scikit-learn, Pandas) to forecast customer churn and purchasing behavior, improving customer retention by 22% and increasing campaign ROI by 30%.
SQLPythonScikit-learnPandasPower BIETLPredictive Modelling
Academic

Teaching Assistant — OOP, Data Structures & Algorithms, Databases

Concordia University

January 2024 – September 2025
Montreal, QC, Canada
  • Used Python (Pandas, NumPy) to clean, transform, and validate raw datasets, reducing manual data preparation effort by 45% and improving analytical turnaround time.
  • Automated repetitive data cleansing and transformation tasks using Python scripts, reducing recurring analyst effort by 30+ hours per month across reporting cycles.
  • Worked with Snowflake and BigQuery to process and analyze high-volume cloud-hosted datasets, improving access to scalable analytics-ready data across cross-functional teams.
  • Developed and maintained cloud-based analytical datasets that improved query efficiency by 32% and supported faster downstream reporting and business analysis.
PythonPandasNumPySnowflakeBigQuerySQLData Cleaning
Industry

Data Analyst

Tech Mahindra

August 2020 – July 2023
India
  • Supported migration of on-premise analytical workflows into cloud-based environments, improving scalability, maintainability, and long-term reporting efficiency.
  • Improved overall data quality by 30% by implementing validation rules, reconciliation checks, duplicate detection logic, and source-to-target consistency controls.
  • Built and supported ETL/ELT workflows for ingesting and transforming data from multiple sources, reducing data preparation turnaround time by 40% and improving reporting readiness.
  • Performed A/B testing analysis on product and user journey enhancements using SQL and Python, contributing to a 12% improvement in conversion rate through data-backed optimization recommendations.
SQLPythonETLData QualityA/B TestingCloud MigrationAzure

Certifications

Continuous learning through industry-recognized certifications and courses.

Microsoft Certified: Power BI Data Analyst Associate – PL-300

Microsoft

Completed

Microsoft Certified: Azure Fundamentals – AZ-900

Microsoft

Completed

The Complete SQL Bootcamp

Udemy

Completed
View Credential

Power BI for Business Intelligence

Udemy

Completed
View Credential

What's Next?

Get In Touch

Open to full-time opportunities in Data Analyst, Data Engineer, Business Analyst, and BI Developer roles across Canada. Whether you have a question, a potential opportunity, or just want to connect, feel free to reach out!

Canada