Hi, I'm Jayesh Patil

Operations data, turned into decisions.

MS in Analytics from Northeastern, MBA in Operations & Supply Chain Management, Lean Six Sigma Green Belt. I build forecasts, Power BI and Tableau reporting, and SQL data models for teams that plan around the numbers.

Download resume See my journey
Jayesh Patil
Open to analyst roles, Boston and beyond

At a glance

From internships and projects
40+datasets in automated reporting at Dottir Labs
24,350recipient profiles built from 65,002 grant records

One finding from the CRM segmentation

Recipients
19%
Funding
74%

The top segment was 19% of recipients but received 74% of funding.

About

I started in operations and supply chain, then went deep on statistics and modeling. Most of my work sits between the two: taking messy operational data, getting it right, and turning it into something a team can plan around.

That has meant forecasting daily demand for staffing decisions, mapping alternate shipping routes and measuring the trade impact of the Suez Canal blockage, building a SQL data warehouse so reporting stops double-counting, and segmenting 24,000+ grant recipients so an outreach team knows where to start.

On more than one project, the most useful thing I found was a bug in the data, not a pattern in it. Checking the data before trusting the result is the habit I bring to every team.

Tools I use most

  • Power BI
  • Tableau
  • SQL (MySQL)
  • Advanced Excel
  • Python
  • R
  • scikit-learn
  • Power Query

Experience & journey

Scroll through the roles and places that got me here. The globe follows along.

  1. 2018 to 2021, Pune, India

    BBA in Marketing

    MIT World Peace University

    Where I started: marketing, consumer behavior, and my first taste of working with data to explain why customers act the way they do.

  2. August to December 2019, Pune, India

    Marketing Intern

    Sahyadri Hospitals Pvt. Ltd.

    • Coordinated cross-functional digital initiatives and campaign reporting in Advanced Excel, improving online visibility by 20%.
    • Ran voice-of-customer analysis and presented findings to leadership, recommending changes that drove a 10% service improvement.

  3. 2021 to 2023, Pune, India

    MBA, Operations & Supply Chain Management

    Indira Institute of Management

    Specialized in operations and supply chain, with business analytics. This is where forecasting, logistics, and process improvement became my core.

  4. May to July 2022, Pune, India

    Logistics Analytics Intern

    Indira Institute of Management

    Project: Optimizing and reducing obstructions at the Suez Canal using analytical tools.

    • Forecast Suez Canal shipping traffic in Power BI and built route maps from port coordinates, identifying alternate shipping routes to reduce transit cost and protect service levels.
    • Quantified operational disruptions and trade impact from the Ever Given blockage using import/export data.
    • Conducted field research on truck and container logistics to identify supply chain bottlenecks, and presented cost and transportation insights to internal and external stakeholders.
    • Owned the engagement end to end, from problem framing and requirements definition through recommendation and handoff.
    • Microsoft Power BI
    • Predictive analytics & forecasting

    Shanghai to Rotterdam via SuezCape of Good Hope detour

    The globe shows the route I mapped in Power BI from port coordinates.

  5. 2024, Mumbai to Boston

    MPS in Analytics, Statistical Modeling

    Northeastern University

    Moved to Boston to go deep on statistics, machine learning, and SQL. The projects further down this page come from this program.

  6. January to April 2026, Somerville, MA

    Analytics Software Engineering Intern

    Dottir Labs

    Focus: Raman spectroscopy data from field-deployed water-monitoring sensors.

    Detection threshold H-O-H bend O-H stretch 0 Raman shift (cm⁻¹) 4000
    Illustrative Raman spectrum of water: the H-O-H bend near 1640 cm⁻¹ and the O-H stretch around 3200 to 3400 cm⁻¹.
    • Partnered with operations and research stakeholders to define reporting requirements across 40+ datasets, and delivered an automated pipeline that improved data quality for real-time monitoring.
    • Delivered a self-service dashboard giving stakeholders KPI visibility across field-deployed sensor data, replacing manual consolidation with automated batch processing.
    • Standardized a detection-threshold reporting framework with validation and fault-recovery controls, enabling automated recurring reporting and reducing manual analysis effort.

  7. Now, Boston, MA

    Looking for what's next

    MPS in Analytics, Northeastern University

    Open to data analyst, BI analyst, business analyst, and supply chain analyst roles, in Boston and beyond.

    Get in touch

Projects

Three featured projects closest to operations and BI work, then two more on modeling.

October 2025Forecasting

Operational Forecasting of Daily Demand, San Francisco

Forecast daily operational volume from administrative records so district teams could plan short-term staffing and scheduling.

  • Python
  • scikit-learn
  • pandas
How I built it
  • Rebuilt timestamps and mapped district codes to turn 905K+ raw records into a clean operational dataset.
  • Built a lagged regression forecaster for daily counts.
  • Modeled search likelihood with logistic regression (test ROC-AUC 0.765) and multiclass outcomes with a random forest.
  • Put one-hot encoding, median imputation, and QA checks into reproducible pipelines.
905K+records
28MAE, daily counts
35RMSE
2026, capstone for YSSL Inc.BI & segmentation

CRM Profiling & Audience Segmentation

Turned six public grant datasets into a CRM-ready profile table, then segmented recipients so the outreach team knew where to focus.

  • RFM
  • Power BI
  • Data governance
My part of the work
  • Profiled and cleaned six public sources and consolidated 65,002 inflation-adjusted (CPI) grant records from 2017 to 2024 into 24,350 recipient profiles.
  • Built RFM (recency, frequency, monetary) profiles and four outreach segments.
  • Wrote the data quality and governance checks, and built some of the Power BI report pages.
  • Designed the source-validation layer that traces every compliance recommendation to its government source.

Team of five. Teammates handled the CIPO, NAICS, and O*NET enrichment.

24,350profiles
74%funding to top segment
19%of recipients
View repository
November 2025SQL & data modeling

Pharmacy Claims Data Warehouse & Reporting

Designed a MySQL dimensional model for raw pharmacy claims and wrote the reporting queries that run on top of it.

  • MySQL
  • CTEs
  • Window functions
How I built it
  • Normalized raw claims data to third normal form (3NF) with primary and foreign keys and referential-integrity rules.
  • Wrote SQL reporting on drug utilization, cost by age segment, and latest fill per member.
  • Found and fixed empty fill records that were inflating utilization counts.
1fact table
4dimension tables
3NFnormalized
View repository

More projects

October 2025Machine learning

Predictive Modeling of Stop Outcomes, Saint Paul, MN

Compared four classifiers on 675,156 records and used SMOTE for class imbalance so the model caught rare outcomes, not just common ones.

How I built it
  • Engineered time and demographic features in pandas and NumPy.
  • Built and compared logistic regression, random forest, XGBoost, and a stacked ensemble (MLP and XGBoost with a logistic regression meta-learner).
  • Explained model behavior with feature importance and confusion matrices in Matplotlib and Seaborn.
0.943ROC-AUC
0.945accuracy
0.77minority recall
Graduate team projectMachine learning

Traffic Crash Injury Prediction & Crash Archetypes

Predicted crash injury severity and grouped recurring high-risk patterns into archetypes by time, location, and conditions. Along the way I caught a capitalization bug that had split five severity levels into ten classes.

My part of the work
  • Removed outliers with the IQR method, from 195,092 to 182,237 rows.
  • Ran the exploratory analysis and built the SVM classifier and K-means clustering.
  • Fixed the severity-label inconsistency before modeling.

Team project. Teammates built the gradient-boosting models.

182Kclean rows
10 to 5severity classes fixed
SVMplus K-means
View repository

Community & interests

Hackathons, meetups, and what I'm learning next.

  • March 2026

    MIT Hacking Medicine GrandHack 2026

    Participant, Portable Health track.

  • 2024 to present

    GDG Cloud Boston

    Community member, and DevFest Boston attendee from 2024 to 2026.

  • 2024 to 2026

    AI agent workshops

    Agentverse (Google Cloud Labs) and Build with AI Boston.

At work

  • AI agents & automation
  • Healthcare analytics

Off the clock

  • Music
  • Movies
  • Reading
  • Sports

Currently learning

  • Building an AI agent for data analysis (text-to-SQL)
  • Power BI DAX, working toward the PL-300 certification
  • A/B testing and experimentation
  • A first Kaggle competition submission

Skills

Grouped by how I use them.

Analytics & BI

  • Power BI
  • Tableau
  • Advanced Excel PivotTables, Power Query
  • SQL MySQL, SQLite

Languages & modeling

  • Python pandas, scikit-learn
  • R and Julia
  • Regression, classification
  • Time-series forecasting

Operations

  • Demand planning
  • Process optimization
  • Cost and variance analysis
  • Supply chain bottleneck analysis

Business analysis

  • Requirements gathering
  • Process mapping, gap analysis
  • KPI definition, UAT
  • Agile/Scrum

Education & certification

  1. 2026

    Master of Professional Studies in Analytics

    Northeastern University, Boston, MA. Concentration in Statistical Modeling.

  2. 2023

    MBA, Operations & Supply Chain Management

    Indira Institute of Management, Pune, India. With Business Analytics.

  3. 2021

    BBA, Marketing

    MIT World Peace University, Pune, India.

Certification

Lean Six Sigma Green Belt

Issued by Anexas. Process improvement with DMAIC, root-cause analysis, and statistical process control.

Next up: Microsoft PL-300 (Power BI Data Analyst), planned.

Let's talk

I'm looking for data, BI, business, and supply chain analyst roles. If you're hiring or want to talk through a project, send a note and I'll reply within a day or two.

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