Mansha Mahtani

Mansha Mahtani runs the data organisation for the business-banking side of Monzo, the coral-card bank that has become a fixture of British wallets, after a decade that carried her from Mumbai to Philadelphia, New York, Silicon Valley and London. What made us look twice wasn't the logos on the résumé but its shape: she keeps arriving in rooms before the furniture does, and she got to numbers by way of the art studio.

A designer's way into numbers

Most people who end up leading data teams arrive through statistics, physics or a doctorate. Mansha came through Penn's Digital Media Design programme, an engineering degree that splices computer science together with fine art and is better known for supplying Pixar and DreamWorks with technical directors than for producing bankers. She paired it with a minor in consumer psychology. Her first listed job, taken while still a student, carried the title "creative head" at a Wharton-incubated start-up that compared book prices across Indian online shops; she designed the interface. Her undergraduate research was on how to visualise financial data.

Line those up and you get a particular kind of data scientist: one who treats a chart as a sentence rather than a receipt. It shows in a detail that is easy to skim past in her early career. At Blue Apron she didn't just define the company's customer-value metric; she built self-serve tools so that colleagues in marketing could read the numbers without a data scientist in the room. Making figures legible to people who don't work in figures is a design instinct, and it's rarer in this field than it ought to be. It's also, we'd guess, a large part of why she rose through management rather than staying a solo analyst: the person who can make the numbers land is the person the room keeps inviting back.

The empty room

In 2015, "data scientist" was a job title barely three years into being fashionable, and Blue Apron was one of the hottest start-ups in New York, shipping boxes of pre-portioned ingredients before the meal kit became a cliché. Mansha left a consulting job at EY to become the company's first data science hire: no team, no tooling, no precedent. She wrote the A/B testing tool herself, in R, and helped grow the analytics function to fourteen people.

What's telling is that the pattern repeated inside a company where it didn't need to. At Instagram and then Meta, among tens of thousands of colleagues, she kept gravitating to the newest corners: the first data science team for Meta's on-platform shopping ads, the zero-to-one launches that let creators get paid directly by their fans. Then, in late 2023, she left the giant for Monzo's business-banking arm, a smaller business growing at close to fifty per cent a year, and within eighteen months was its Director of Data.

Three companies, three versions of the same choice. It reads less like restlessness than a preference. Being first means your own judgement, not an inherited playbook, decides what gets measured and what gets ignored, and that is a muscle you can only build by using it. Plenty of capable people find that prospect frightening. Mansha appears to find it the point.

Building the bench

There's a less visible thread running alongside the firsts. Two years into her data career she had already interviewed more than forty candidates and was training a team from scratch. At Meta she ran the EMEA data science internship programme as its director, selecting fourteen managers, scoping fourteen projects and running the calibration that decides who gets an offer. In between, she lent her time to guides written for people trying to land their first data science job, the entry rung that senior people tend to forget once they've climbed past it.

Taken together, this is someone who builds the bench before the building needs it. It's a practical philosophy as much as a generous one. The reason she has been free to walk into the next empty room, three times over, is that each time she left behind a team that no longer required her. That is the trade most careers never make explicit: the more thoroughly you make yourself unnecessary, the more interesting the next job you're allowed to take.

Money has gravity

Consumer tech measures attention. A bank measures money, and the difference changes the weight of every decision. At Instagram, Mansha evaluated one of the most discussed experiments of its era, the hiding of like counts, to see whether it changed how people discovered new brands and creators. Fascinating work, with soft consequences. She also built models to detect fake accounts and coordinated campaigns around the 2020 US election, which was the first time her toolkit carried civic stakes. At Monzo Business, the users are plumbers, florists, freelancers and the more than 700,000 small firms that bank there, and a wrong signal in a lending or fraud model lands on somebody's rent. The trade-off between false alarms and missed ones, a staple of the interview questions she once helped newcomers prepare for, stops being a textbook exercise.

There's a pleasing symmetry in where she has landed. She grew up in Mumbai, a city that runs on small enterprise, and now owns the data for Britain's. And she is in the chapter of a career where the job inverts: from doing the analysis to deciding what is worth analysing, from being the first hire to deciding who the first hires are. With Monzo pushing into Europe, a leader who has rebuilt her working life in one country after another, and who can draw a chart that a florist understands, is exactly the kind of person a bank should want in that seat. We'll be watching what she measures next.