Jess Lachs

AI can be used to scale data access by enabling non-technical users to generate and edit their own queries.

"Working to build these tools that will help not just our team in terms of time saving... but really to be able to empower non-technical users to be able to do things on their own and not have to take..."

Curiosity is a non-negotiable trait for top data talent as it drives proactive insight discovery.

"I really look for that curiosity and that self-motivation to do it without being told. ... The person that has that curiosity, something seems off, something doesn't really make sense and goes and pro..."

A candidate's ability to handle feedback and pivot their thinking is a key indicator of their future performance in ambiguous environments.

"Seeing how people react to being told they're wrong is a really important signal in my opinion. Seeing how people respond, how they're able to take new information and pivot, how they're able to make..."

Analytics should be positioned as a proactive partner that drives business decisions rather than a reactive service that only answers tickets.

"For me, analytics is a business impact driving function and not purely a service function, not just answering the why, but answering the, 'What do we do now that we know this?'"

A centralized reporting structure for data teams preserves talent standards and career growth while maintaining alignment through cross-functional 'pods.'

"I believe a central model, a center of excellence is superior... we have a central analytics team, but we are divided up into pods that map perfectly with how product engineering, operations marketing..."

High-performing teams exhibit 'extreme ownership' where members step outside their technical roles to solve the core business problem.

"Yes, you are a data scientist, but your goal is to figure out what's happening. And if that means that you're going to pick up the phone and call customers, then that is what you're going to do to rol..."

Translating all business levers into a 'common currency' (like Gross Order Value) allows for objective trade-offs across different departments.

"We spend a lot of time quantifying things in terms of a common currency. ... if we have, say, a dollar to spend, we know what we get depending on where we put it, over what timeframe."

Avoid using lagging indicators like retention as primary goals; instead, identify and move the short-term input metrics that predict them.

"Retention is a terrible thing to goal on. It's almost impossible to drive in a meaningful way in a short term. Ultimately, you want to find a short-term metric you can measure that drives a long-term..."

Simple, intuitive metrics are more effective at driving organizational behavior than complex composite scores.

"Keeping things simple is another thing I've learned... if people understand it, if they have an intuition around it, if it's something that people can talk about across the company, it's going to be a..."

Averages can hide critical business failures; teams should set specific goals to eradicate 'fail states' or 'disaster' experiences.

"It's so important to find these edge cases in these fail states and actually set concrete goals around eliminating them because it can be really powerful."

Exploratory data work requires dedicated, protected time to prevent it from being crowded out by reactive requests.

"You have to be very intentional to carve out time for exploratory work for deep dives because as you mentioned, there are always more questions and more work to be done than hours in the day."

Effective prioritization requires making the trade-offs of new requests visible to stakeholders.

"When something comes up to be able to say, 'Hey, this data poll that you want me to do, is this more important than these other three things that I was going to be working on? Yes or no?'"

When quantitative data fails to explain 'why' a feature didn't work, data teams should pivot to direct customer conversations.

"The team, data scientists included, just sat and made phone calls. ... that's where qualitative research is superior to quantitative research, it's asking for the context, to actually talking to peopl..."