The deliberate pivot · AI & data science

Experience taught me how systems behave.Now I'm learning how machines learn.

I'm Mosa Rahimi—a Wharton MBA, Harvard MPA, and Amazon Leo leader. After two decades in operations, policy, and strategy, I'm deliberately building at the intersection of artificial intelligence, finance, and the consequential problems those systems create.

Artificial intelligenceDeep learningEconomic modelingData science
20+

years across public service, policy, technology, and operations—now applied to AI

Mosa Rahimi in a dark suit
Based in the United StatesAmazon Leo · Project Kuiper
AI & DataOperations LeadershipStrategic SystemsPublic ServiceCross-Cultural Leadership

Selected impact

Measured in outcomes.

The settings have changed—from border security to advanced manufacturing—but the work has remained consistent: make the system legible, align people, and move the mission forward.

01364K

units stowed

A non-peak Amazon record

0270+

programs coordinated

Across all 34 Afghan provinces

0312K

person border force

Scaled from 5,000 personnel

0440%+

faster reporting

Through operational systems design

Why this pivot

Not reinvention for its own sake.A deliberate expansion of how I solve.

Operations taught me how large systems coordinate under pressure. Policy taught me how institutions shape outcomes. Strategy taught me where leverage actually lives. AI adds a new technical language—and a new set of consequential problems—at the intersection of finance, governance, and human-scale impact.

Machine learningAI policyApplied data scienceSystems thinking

The journey

One throughline.Many arenas.

01

June 2025 — Present

Amazon Leo (Project Kuiper)

Redmond, Washington

Coordination Supervisor

Coordinating production for Amazon Leo (Project Kuiper)—building the manufacturing systems behind the satellite constellation and translating complex aerospace operations into dependable human-scale execution.

02

2024 — 2025

Amazon

Philadelphia, Pennsylvania

SSD DC Area Manager II

Led high-volume inbound and outbound operations while building confidence, capability, and data fluency across frontline teams.

  • Raised a non-peak inbound record from 350K to 364K units—more than 40% above daily goal.
  • Turned outbound palletize into one of the network’s most consistent operations.
  • Built an hourly Excel performance tool and developed four process assistants.
03

2019 — 2025

Dastranj

Philadelphia, Pennsylvania

Founder & CEO

A startup with a long-term thesis: apply AI, machine learning, and computer vision to the artisan goods market—building the supply chain, brand, and operating systems to connect craft producers with global demand.

  • Built an end-to-end supply chain from producer relationships through fulfillment.
  • Company mission centers on scaling artisan goods through technology—not reinvention, but a deliberate bet on AI in a category that still runs on trust and handwork.
04

2021 — 2022

Harvard Kennedy School

Cambridge, Massachusetts

Belfer Young Leader Fellow · Machine Learning Teaching Assistant

Researched international security and science policy while helping students connect machine-learning theory to working code and final projects.

05

2019 — 2021

Team Afghan Power · Refugee Investment Network

Philadelphia · Washington, D.C.

Strategy & Development

Helped shape a five-year micro-grid and internet expansion strategy and supported capital access for refugee entrepreneurs.

06

2016 — 2018

CyraCom

New York City

Farsi–Dari Interpreter

Served as the center’s sole in-house Farsi–Dari interpreter across law, finance, medicine, and emergency response; evaluated 100+ applicants and eliminated outsourcing costs.

07

2015 — 2016

A new beginning

New York

Bank teller · Translator · Warehouse worker · Cashier

The transition period: rebuilding from the ground up in America while staying focused on education and the long horizon.

08

2010 — 2014

DOJ / ICITAP

Kabul, Afghanistan

Adviser & Senior Program Assistant

Coordinated more than 70 capacity-building programs across 34 provinces and aligned 30+ government, diplomatic, and civil-society stakeholders.

  • Reduced bureaucracy and overlapping projects by 20%.
  • Cut provincial reporting time by more than 40%.
  • Helped design strategic planning, international relations, and monitoring units.
09

2008 — 2010

U.S. Army Central Command

Kabul, Afghanistan

Cultural Adviser & Interpreter

Advised senior leaders on culture, law, and policy; interpreted daily for high-level delegations and taught leadership, anti-corruption, English, and technology.

10

2004 — 2008

Afghan Border Police

Kabul, Afghanistan

Aide-de-Camp · Chief of Staff

Supported the Director General as the force grew from 5,000 to 12,000 personnel across 19 provinces, 14 crossings, and four international airports.

Education

Policy mind. Business lens. Technical curiosity.

A dual graduate journey at Wharton and Harvard built the bridge between markets, institutions, analytics, and public leadership.

W
2019 — 2022

The Wharton School

MBA

Finance · Business Analytics · Management

H
2019 — 2022

Harvard Kennedy School

MPA

Public leadership · Policy · Technology

A
2009 — 2013

American University of Afghanistan

BBA

Finance

K
2003

Kabul National Police Academy

Police Sergeant

Border Police

My story is a humble journey of survival and triumph over some of the toughest challenges refugees and ethnic minorities encounter every day.

Citizen by choice

Resilience is not a chapter. It is the operating system.

As a refugee child in Iran, I heard stories of technological progress over the radio. Years later, after serving at the center of Afghan public institutions, I came to America and started again—from minimum-wage work, without a professional support network.

I chose to share that transition, not hide it. It shaped how I lead: with empathy for the person behind the metric, respect for the invisible work, and the conviction that capability is often waiting for opportunity.

Mosa Rahimi with his family during his childhood in Iran
Family portraitIran · The early years
A family photograph from Mosa Rahimi's childhood in Iran
Growing up togetherIran · Family archive

Before the boardrooms, institutions, and operations floors, there was family—the first system of resilience, responsibility, and hope.

Story 02 · The impossible dream

College was not in the cards.I refused to stop dreaming.

The chance of going to college felt nonexistent. So I worked night and day—through dust, grease, fields, and machines—while holding onto a future no one around me could promise.

The work covered my clothes. It never touched the dream.
A young Mosa Rahimi standing beside a red tractor
Work was the reality.Long days · No shortcuts
A young Mosa Rahimi standing in a field in work clothes
College was the dream.Out of reach · Never out of sight

Story 03 · Service under fire

I put my life on the line.The dream was bigger than the danger.

For eleven years, service meant accepting real risk—from border provinces to counter-narcotics missions across Afghanistan. Every journey carried uncertainty, but the dream was never only personal: a safer, stronger future built through institutions that could truly serve people.

The danger was real. So was the future I could see beyond it.

Story 04 · The long road to the classroom

In 1999, college was impossible.In 2022, I graduated from Wharton and Harvard.

23years from dream to dual degrees

There was no straight line—only work, service, migration, restarting, and the decision to keep going. The journey moved through the American University of Afghanistan and, eventually, two graduate programs at Wharton and Harvard Kennedy School.

Distance is not destiny. Sometimes the longest road produces the clearest purpose.
Mosa Rahimi celebrating his graduation from the American University of Afghanistan
AUAFBBA · Finance · 2013
Mosa Rahimi crossing the stage at his Wharton MBA graduation
WhartonMBA · 2022
Mosa Rahimi with family after the Wharton graduation ceremony
The moment afterA dream shared
Mosa Rahimi celebrating his Harvard Kennedy School graduation
Harvard Kennedy SchoolMPA · 2022
1999 The dream2013 AUAF2022 Wharton + HKS
Across cultures

Farsi Native

English Full professional

Pashto Professional working

Technical work

Something to examine.Not just a résumé.

AI companies, policy organizations, and technical recruiters need artifacts—not adjectives. Here is code, analysis, and work you can inspect before we talk.

For AI teams & technical recruiters

Examine the work.Then let's talk.

I'm looking for roles and collaborations at the intersection of artificial intelligence, operations, and policy. Start with the artifacts above—or reach out directly if you see a fit.