Based in Dublin · Open to opportunities
RahulPagar
Senior Data Analyst · MSc Business Analytics
5+ years turning raw enterprise data into decisions — SQL, Python, Power BI, Machine Learning. From manufacturing floors at Škoda VW & Caterpillar to EV grid forecasting and healthcare risk prediction.
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5+Years experience
13GitHub projects
40%Query speed gain
MScBusiness Analytics
Currently available · Dublin, Ireland
01
About · Profile
WHO I AM
I'm a Senior Data Analyst with 5+ years of enterprise experience transforming complex datasets into decisions that move the needle — across manufacturing, automotive, and now healthcare and fintech.
My background spans end-to-end analytics delivery: from raw data pipelines and star-schema modelling to predictive ML systems and executive Power BI dashboards. I've worked inside large-scale enterprise environments at Škoda Auto Volkswagen, Caterpillar India, and Mahindra & Mahindra, consistently bridging the gap between technical complexity and business clarity.
Currently based in Dublin, holding an MSc in Business Analytics (2:1) from Dublin Business School. Actively targeting roles in Data Analytics, BI Development, Analytics Engineering, and Healthcare IT / FinTech.
Full Stack AnalyticsML EngineeringBI DevelopmentETL DesignData StorytellingStakeholder Comms
🏭
Enterprise Background
3 large-scale enterprise employers across automotive and manufacturing — Škoda VW, Caterpillar India, M&M India.
🤖
ML + BI Hybrid
Rare combination of deep BI expertise (Power BI, DAX, star schemas) with hands-on ML delivery (SVR, XGBoost, NLP).
🎓
MSc Business Analytics
Dublin Business School, 2:1 — Applied Statistics, Data Mining, ML, Financial Analytics, Power BI & Tableau.
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Dublin-Based, Global Mindset
Originally from Pune, India. Working in Dublin — open to hybrid & remote roles across EMEA.
02
About · Arsenal
TECHNICAL SKILLS
Languages
PythonSQLDAXM Query
Frameworks & Libs
Scikit-learnXGBoostPandasNumPyMatplotlibTensorFlow
BI & Visualisation
Power BITableauDAX CalcExcel (Adv)
Databases
MS SQL ServerMySQLStar SchemaSnowflake
ML Techniques
SVRRandom ForestNLPTime SeriesClassification
Data Engineering
ETL PipelinesFeature Eng.Data CleaningAPI Integration
Tools & Workflow
GitJIRAJupyterGoogle ColabVS Code
Soft Skills
Stakeholder MgmtRequirementsAgile / JIRAStorytelling
03
Career · Work History
EXPERIENCE
Nov 2022 – Aug 2024
Škoda Auto Volkswagen India
Pune, India
Senior Data Analyst
- Designed interactive Power BI dashboards consolidating data from multiple enterprise systems, improving leadership reporting accessibility and decision-making efficiency by an estimated 30%.
- Built and optimised SQL-based data models (star schemas) and ETL workflows feeding executive reporting layers, reducing query runtimes by 40% and improving downstream reporting accuracy.
- Developed predictive forecasting models in Python (regression, time-series) for demand and resource planning, improving planning accuracy by 18%.
- Built supervised ML models to detect consumption anomalies and surface optimisation opportunities, contributing to 7% cost savings on operational spend.
- Automated recurring analytics pipelines and collaborated cross-functionally to translate ambiguous business requirements into structured BI solutions delivered on time.
Power BISQLPythonStar SchemaETLMachine LearningDAX
Oct 2021 – Nov 2022
Caterpillar India
Pune, India
Data Analyst
- Delivered targeted analytics use cases on operational, quality and event-level datasets, identifying inefficiencies that contributed to a 12% cost reduction.
- Built Power BI dashboards tracking key operational KPIs, enabling leadership to monitor trends in real time.
- Performed trend, variance and root-cause analysis on historical datasets uncovering recurring failure patterns — resulting in a 15% reduction in repeat issues.
- Developed predictive statistical models in Python to estimate failure probability and risk prioritisation using incident logs and quality datasets.
- Built and evaluated supervised ML models (classification and regression) improving early issue detection accuracy by 24%.
Power BIPythonXGBoostRoot Cause AnalysisKPI DashboardsClassification
Oct 2019 – Oct 2021
Mahindra & Mahindra India
Pune, India
Operations Analyst
- Collected, cleaned and prepared large-scale operational and sensor datasets using Python and SQL, ensuring data accuracy, consistency and reliability for downstream analysis.
- Worked closely with cross-functional teams to gather requirements and translate business problems into structured analytical solutions and reporting deliverables.
- Applied descriptive and diagnostic analytics to explain performance variations and deviations, supporting data-driven course corrections.
- Built and maintained KPI dashboards covering productivity, cycle time, quality and efficiency metrics, surfacing trends for management review.
PythonSQLKPI DashboardsSensor DataStakeholder MgmtETL
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Academic · Education
EDUCATION
★ Post Graduate
MSc in Business Analytics
Dublin Business School
Sep 2024 – Sep 2025 · Dublin, Ireland
2:1 DistinctionApplied Statistics & Machine Learning · Data Mining · Financial Analytics · Business Intelligence & Data Visualisation (Power BI, Tableau) · Python & SQL · Project Management · Requirements Analysis · Business Strategy
Undergraduate
Bachelor of Engineering
Savitribai Phule Pune University
Jun 2011 – Jun 2015 · Pune, India
First Class with DistinctionCertifications
Oracle Cloud Infrastructure (OCI) — Data Science Professional
Oracle
Google Advanced Data Analytics Professional Certificate
Google / Coursera
Post Graduate Program in Data Science
Purdue University
Python for Data Science
IBM
Machine Learning for Data Science
Simplilearn
Data Visualisation Using Tableau
Simplilearn
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Impact · Metrics
BY THE NUMBERS
5+
Years enterprise
experience
30%
Reporting efficiency
improvement (Škoda VW)
40%
SQL query runtime
reduction delivered
24%
Early issue detection
accuracy improvement
06
GitHub · Selected Work
PROJECTS
↗01★ MSc DissertationMachine Learning
Check remaining projects on GitHub →EV Charging Peak Load Prediction
End-to-end ML forecasting system predicting station-level monthly peak electricity demand across an EV network using 10+ years of historical data and Open-Meteo weather API. Benchmarked Linear Regression, SVR, Random Forest, XGBoost, and Neural Networks with grid search cross-validation. Outputs translated into grid infrastructure planning insights.
PythonScikit-learnXGBoostSVRNeural NetworksOpen-Meteo APIPandas
↗02Healthcare MLHeart Attack Risk Prediction
Classification models predicting heart attack risk for insurance underwriting, prioritising recall to minimise false negatives. Includes a cost-benefit ROI framework comparing traditional vs ML-augmented screening.
PythonXGBoostLogistic Reg.KNNScikit-learn
↗03Power BICybersecurity Threat Dashboard
Executive Power BI dashboard monitoring cybersecurity incidents, vulnerabilities, and financial impact across business units. Star-schema data model with advanced DAX measures for incident frequency and severity scoring.
Power BIDAXStar SchemaData Modeling
↗04Regression StudyRegularisation & Model Comparison
Systematic regression benchmark for house price prediction — Linear, Lasso (L1), Ridge (L2), Elastic Net, SVR, Random Forest — with GridSearchCV tuning and bias-variance analysis across model families.
PythonLasso/RidgeElasticNetSVRGridSearchCV
↗05FinTech MLBank Term Deposit Prediction
Supervised ML predicting customer subscription to term deposits. Implements SMOTE for class imbalance, full feature encoding pipeline, and thorough evaluation across multiple classifiers.
PythonSMOTEClassificationFeature EncodingPandas
↗06AI ToolShortlist — AI CV Optimizer
Browser-local TF-IDF ATS scoring tool with Gemini 2.5 Flash-Lite AI rewriting backend, cover letter generation for 13 markets, interview Q&A generation, and PDF/DOCX export. Live at shortlistcvbuilder.netlify.app.
JavaScriptTF-IDFGemini APINetlify FunctionsPDF Export
Let's work together
Got a project
in mind?
in mind?
I'm currently open to new Data Analyst, BI Developer, Analytics Engineer, and Healthcare IT / FinTech roles in Dublin and remote. Let's build something meaningful with data.