Machine Learning Business Intelligence

AI-Powered resume reviewer application August ****- May 2024

University of Toledo.

Built a web-based resume reviewer Application leveraging Google’s Gemini Pro LLM Model. Key Features : Resume Parsing, skill matching, machine learning capabilities. Technical Implementation: Python language, Google Gemini pro LLM model, python libraries, Database - MYSQL. Technical Architecture: Input as candidate resumes, Processing using Gemini pro analysis, output- candidate ranking report, scoring mechanism based on the requirement.. Challenge addressed : Reduced manual screnning time, minimize human bias, improvement recruitment precision.

(+1 ) 419-***-**** ************@*****.*** www.linkedin.com/in/ganesh-mirke GANESH MIRKE

TECHNICAL SKILLS

Languages : Python, SQL, C, C++, R programming, SAS Programming Libraries: Numpy, Pandas, matplotlib, seaborn, plotly, scikit-learn, scipy, statsmodel, pytorch, Tensorflow. Applications: PowerBI, Tableau, MS Excel, SAP, Alteryx. Concepts: Advance data structures and algorithms, Probability and applied statistics, data science pipeline, NLP, MLOP, ETL, KMeans, boosting/Bagging models, statistics and hypothesis testing, advance analytics concepts. Finance : Financial Modeling, Income and cash flow statement analysis, Investment Analysis, Risk Assessment. Process : Agile, Scrum, Kanban.

Business Skills: Self-starter, Quick Learner, Technical Adaptability, Analytical skills, project management, critical thinking, Independent thinking, ability to identify problems, strong communication, Reliable, Responsible, Flexible, Solution oriented.

WORK EXPERIENCE

Data Analyst (3+ years of experience - Insurance Customer data) March 2019 - September 2022 Accenture. on-site

Built and deployed predictive models for business intelligence and analytics. Designed and optimized deep learning models for real-time applications. Created automated pipelines for ML model deployment and monitoring. Used advanced statistical methods to evaluate model performance and improve accuracy. Collaborated with cross-functional teams to develop scalable AI-driven solutions. Worked cross-functionally with software engineers and AI researchers to integrate ML solutions. Developed debugging tools and workflows to improve AI system interpretability and efficiency. Applied advanced statistical analysis for model evaluation and fine-tuning. Jr. Data Scientist. December 2017- February 2019

Infosys

Processed, cleansed and verified the integrity of data used for data analysis using SQL and Python. Analyzed and presented results in a clear manner.

Built and optimized the state-of-the-art machine learning and deep Learning models. learnt how to create and automate the project life cycle with the help of creating data pipelines. Created interactive dashboards visualizing complex business insights using Python and Tableau. on-site

PROJECTS

AllianceOne

Developed and fine-tuned Transformer-based models using PyTorch and TensorFlow. Designed, trained, and deployed large-scale machine learning models using Hugging Face. Optimized model performance through hyperparameter tuning and experimentation. Created and curated large-scale datasets, leveraging synthetic data generation techniques. Deployed ML models in production environments, ensuring scalability and reliability. IT Agent

September 2024 - Present

on-site

EDUCATION

Masters of Applied Business Analytics, Univeristy of Toledo Relevant coursework: Data analysis, Data visualization, Business Intelligence management, supply chain, Operations, Financial Analysis.

Bachelors of Science in Information Technology

Relevant coursework: C, C++, OOPS, Python, MySQL, Software life cycle. May 2024

February 2017

COURSES &CERTIFICATES

UDEMY- Data science real world projects in python. UDEMY - SQL- MySQL for data analytics and Business Intelligence. AWS Training and Certification - Fundamentals of ML & AI, Developing ML solutions, Introduction to Amazon SageMaker.

Currently doing AWS AI Practitioner certification. University of Toledo.

.Conducted comprehensive research to analyze and address the challenges of ERP system misfits encountered by small and medium Enterprises (SMEs).

Research Paper August 2023- May 2024

University of Toledo

Performed and presented comprehensive analysis of Netflix content Library- movies and TV shows dataset. Extracted insights about content trends, genres and production. Key analysis objectives: content distribution analysis, temporal trends, Geographical insights.,Visualization created using PowerBI.

Technical skills demonstrated: Data cleaning, Exploratory data analysis, statistical analysis, Technical stack: Jupyter notebook for analysis, python libraries, matplotlib and seaborn for visualization. key findings: movies constitute 69.6% of content, Top genres- dramas, comedies and documentaries, USA & India top content producers.

Business Intelligence Project - Netflix data analysis November 2023

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