Data Analyst Machine Learning

AKSHAY BHARGAV KULAKARNI

+1-513-***-**** ****************@*****.*** LinkedIn Portfolio Git Hub PROFESSIONAL SUMMARY

• Insightful and detail-oriented Data Analyst with 4 years of experience translating complex datasets into actionable insights across education, enterprise SaaS, and energy sectors.

• Proficient in SQL and Python for data wrangling, statistical analysis, and automation of reporting workflows to support business decision-making.

• Skilled in building interactive dashboards and performance reports using Power BI, Tableau, Excel, and Google Data Studio.

• Delivered high-impact analysis for customer behavior, fraud detection, and lead scoring, improving operational efficiency and strategic planning.

• Experienced in A/B testing, hypothesis testing, and KPI tracking to evaluate business initiatives and optimize performance metrics.

• Hands-on expertise in ETL pipelines, data modeling, forecasting, and time series analysis using tools such as Azure Data Factory, MLflow, and BigQuery.

• Adept at collaborating with cross-functional teams and presenting analytical findings to both technical and non-technical stakeholders.

• Strong foundation in Agile workflows, data storytelling, and stakeholder engagement to drive adoption of data-driven practices across departments.

TECHNICAL SKILLS

Programming & Data Analysis: Python, SQL, Pandas, NumPy, Data Wrangling, Data Cleaning, Data Manipulation, Exploratory Data Analysis

(EDA), Feature Engineering, Statistical Analysis, Shell Scripting, Automation Scripting, Web Scraping (BeautifulSoup, Selenium). Data Visualization & BI Tools: Power BI, Tableau, Microsoft Excel (Pivot Tables, VLOOKUP, Power Query, Charts), Google Data Studio, Matplotlib, Seaborn, Plotly, Dash.

Analytics & Reporting: KPI Reporting, Business Dashboards, Data-Driven Insights, Forecasting, Trend Analysis, A/B Testing, Hypothesis Testing, Ad Hoc Reporting, Data Storytelling, Stakeholder Communication. Databases & ETL: MySQL, PostgreSQL, SQL Server, ETL Pipelines, Data Modeling, Data Integrity Auditing, Data Validation, Data Warehousing

(Snowflake, BigQuery), Azure Data Factory.

Cloud Platforms & Version Control: Microsoft Azure (ML Studio, Data Lake, Databricks, Synapse), Google Cloud Platform (BigQuery, Vertex AI), AWS (S3, Cloud Storage), Git, GitHub, CI/CD, MLflow. Machine Learning Fundamentals (Supporting Analysis): Regression, Classification, Clustering (K-Means, DBSCAN), Feature Selection, Dimensionality Reduction (PCA, t-SNE), Model Evaluation (Confusion Matrix, ROC-AUC, F1 Score), Hyperparameter Tuning (GridSearchCV). Office & Productivity Tools: Microsoft Excel, Microsoft Word, Microsoft PowerPoint, Google Workspace (Sheets, Docs, Slides). Operating Systems: Windows, macOS, Linux/Ubuntu.

Core & Soft Skills: Analytical Reasoning, Critical Thinking, Problem Solving, Attention to Detail, Strategic Thinking, Communication, Data Storytelling, Team Collaboration, Stakeholder Engagement, Time Management, Adaptability, Initiative, Presentation, Agile Scrum, Interpersonal Skills, Work Ethic.

EXPERIENCE

Graduate Assistant – CECH Administration

University of Cincinnati, Cincinnati, OH

Jan 2024 – May 2025

• Collaborated with the Director of Institutional Research and CECH data team to support college-wide reporting and strategic decision-making.

• Extracted and cleaned faculty and student data from internal systems using SQL for accurate and timely reporting.

• Designed and maintained Power BI dashboards to visualize key metrics such as faculty workload, enrollment trends, and departmental performance, aiding deans and advisors in data-driven planning.

• Automated Excel-based reporting workflows by developing a SQL–Power BI pipeline, reducing report preparation time by over 60%.

• Performed regular data audits and reconciliations to ensure data consistency and integrity across institutional systems.

• Participated in monthly planning meetings to present actionable insights derived from data trends and reporting analysis.

• Conducted dashboard walkthroughs and trained administrative staff and faculty on data usage, increasing data literacy and adoption across departments.

• Presented key data solutions and reporting outcomes to CECH leadership to guide improvements in reporting efficiency and institutional transparency.

Machine Learning Intern – Microsoft Azure Machine Learning Studio EasyShiksha · Remote

Feb 2024 - Aug 2024

• Worked on the project "Scalable ML Model Automation using Azure" focused on automating end-to-end machine learning workflows.

• Collected, cleaned, and analyzed internal datasets related to user behavior and product interactions for machine learning development.

• Developed and deployed machine learning models for classification, clustering, and recommendation using Azure Machine Learning Studio.

• Designed and implemented automated ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation.

• Utilized Azure AutoML to run multiple algorithms and select the best-performing models based on accuracy and performance metrics.

• Managed model lifecycle, versioning, and deployment using MLflow integrated with Azure ML services.

• Automated ML experimentation workflows, reducing manual processes by 60% and improving model deployment efficiency.

• Created and delivered performance dashboards and reports using Azure Dashboards to communicate insights and model results to stakeholders. Data Scientist

IBM · Hyderabad, Telangana, India (Hybrid)

May 2021 - Dec 2023

• Designed, developed, and deployed machine learning models in Python for customer churn prediction and fraud detection, achieving a 30% improvement in model accuracy.

• Performed data preprocessing, cleaning, and transformation on large-scale datasets using Pandas and NumPy to enable efficient model training and validation.

• Engineered complex features from customer profiles, transaction data, and behavioral patterns to boost model performance and precision.

• Conducted hyperparameter tuning and model optimization using GridSearchCV and k-fold cross-validation to ensure model robustness and generalization.

• Automated end-to-end data pipelines for data ingestion, preprocessing, model training, and reporting using Python and workflow automation techniques, reducing manual errors and improving efficiency.

• Built and delivered interactive data visualizations and insights using Matplotlib, Seaborn, and Power BI to support business decision-making.

• Presented data-driven recommendations to stakeholders to improve customer retention, reduce fraud risks, and enhance lead conversion rates.

• Collaborated in Agile teams, using Git for version control and contributing to machine learning pipeline development and deployment workflows.

PROJECTS

Sales Performance Dashboard

• Developed an interactive Power BI dashboard to track monthly sales, revenue trends, and product performance across regions.

• Cleaned and integrated sales data using Excel, SQL, and Power Query to enable automated reporting.

• Designed visuals and filters for executive-level insights on KPIs, growth rates, and category performance.

• Identified low-performing SKUs and regional gaps, supporting sales strategy optimization. Customer Retention & Churn Analysis

• Analyzed customer behavior using Python and SQL to identify churn drivers and retention opportunities.

• Performed cohort analysis, segmentation, and CLV modeling to uncover churn patterns.

• Built predictive models (Logistic Regression, Random Forest) to score and rank high-risk customers.

• Created retention-focused dashboards and reports for the marketing and CX teams. Marketing Campaign A/B Test Analysis

• Conducted A/B testing on marketing emails to assess the impact of subject line variations on conversion rates.

• Used Pandas and statistical tests (t-test, chi-square) to analyze user engagement and purchase behavior.

• Visualized campaign performance and statistical significance using custom dashboards.

• Recommendations led to a 12% increase in conversion rate for subsequent campaigns. HR Analytics – Workforce Dashboard

• Built a dynamic Tableau dashboard to track workforce metrics including attrition, diversity, tenure, and promotions.

• Aggregated data from multiple sources (Excel, SQL) and performed data cleaning and transformation.

• Enabled HR and leadership teams to monitor trends and make data-informed decisions.

• Reduced manual reporting effort by 50% through automation and dashboard centralization. EDUCATION

University of Cincinnati, Cincinnati, Ohio Jan 2024 – May 2025 Master of Science in Information Technology GPA: 3.9/4.0 Lingayas Vidyapeeth, India Aug 2019 – Jun 2023

Bachelor of Technology in Computer Science Engineering GPA: 3.8/4.0 CERTIFICATES AND ACHIVEMENTS

• Google Data Analytics Professional Certificate from Coursera

• IBM Data Science Professional Certificate from Coursera

• IBM-Certifications:

Python for Data Science, SQL for Data Science, MS Excel, Data Analysis with Python, Data Visualization, Generative AI, Python Project for Data Science,Applied Data Science Capstone.

• Microsoft Press Certificate - Power BI for Data Analysts

• EasyShiksha Internship Certificate - Microsoft Azure ML Studio

• The Sparks Foundation Internship Certificate, Letter of Recommendation.

• Accenture Developer Program Certificate

• Earned Golden Badge in Python and Java on HackerRank.

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