Staff Applied Scientist, AdTech

Launch Potato; Austin, Dallas, Oklahoma City (TX, TX, OK); Hybrid; USD 175,000 - 200,000; Full time

Job summary

Launch Potato, a remote-first company, is seeking a senior data scientist to build models that pair auto insurance shoppers with the right carrier on our click wall and to optimize media spend for ROAS. You will own data, train, deploy, and monitor models in production, starting with auto insurance and expanding to other verticals.

You will work hands-on with an ML engineer, framing problems with business goals, sourcing data, and delivering measurable impact in a fast-paced, remote environment.

Qualifications

• 5+ years of hands-on applied data science with measurable business impact.
• Models used to guide paid media decisions: spend, bidding, or ad serving.
• Built end-to-end models with data collection, deployment, and monitoring.
• Proficient in Python and SQL, with neural network fundamentals.
• Understand how bids shape training data, late labels, and drift.
• Experience with production-grade ML systems is a plus.

Responsibilities

• Build models to decide which carrier each auto insurance shopper sees.
• Own the buying models behind media spend (ROAS-focused).
• Ingest and leverage carrier conversion data in production.
• Frame problems with business context, find data, train, deploy, and monitor.
• Collaborate with an ML engineer on production aspects.
• Plan for expansion to other verticals over time.

Skills

Python

SQL

Data science

Machine learning

Model deployment

Tools

AWS

SageMaker

ECS

S3

Athena

Job description

WHO ARE WE?

Our mission: create predictable, high-value customer acquisition at scale by connecting discovery, intent, and performance across category-leading consumer brands in finance, travel, and entertainment.

We run profitable and bootstrapped, with a South Florida HQ and a remote-first team across 18 countries.

WHY JOIN US?

You own outcomes here, not tasks. We measure work by impact, not activity. The pace is real, and change is constant, so the people who do best turn change into opportunity instead of waiting for it to settle. Feedback runs direct and lands with respect. Ordinary people make themselves extraordinary at Launch Potato.

BASE SALARY: $175,000 to $200,000 per year, paid semi-monthly

YOUR ROLE

You'll build the models that decide which carrier each auto insurance shopper sees on our click wall. The goal is to send every user to the carrier most likely to convert them, so carriers see our traffic convert and raise their bids. You'll also own the buying models behind our media spend, which are held to ROAS.

Carrier conversion data (quotes, policies and acquisition cost) is now coming back to us, and you'll be the one who puts it to work in production. The hard part is the data. Outcomes land weeks or months after the click, many sessions are sparse, the same shoppers come back, and the market drifts. Our bids also decide which users we win, so the model shapes the data it learns from next.

This is a hands-on individual contributor role. You frame problems directly with the business, find your own data, build and validate the model, and stay with it through deployment and monitoring. An ML engineer works alongside you on the production side. Auto insurance takes most of your time to start, and scope broadens to other verticals over time.

We're remote first, and most of the company works East Coast hours.

WHAT SUCCESS LOOKS LIKE

By day 60, you run our insurance marketplace media buying on your own.

By the end of your first year:

• Click wall serving that matches each user to the right carrier
• Automated marketplace bidding taken from proof of concept to scale
• A clear approach for repeat users and sparse sessions
• Production models that hold up through drift and changing objectives
• Output the business trusts and uses without rework

MUST HAVE

• 5+ years of hands-on applied data science with measurable business impact
• Your models drove paid media decisions: spend, bidding or ad serving. Attribution and reporting alone don't qualify.
• You built what's on your resume and can explain it down to the loss function and architecture choice, neural network fundamentals included
• You see how today's bids shape tomorrow's training data, and you've handled late labels, sparse features or drift
• You own models end to end: you find your own data, build through deployment and monitoring, and bring a point of view
• Expert Python and SQL

NICE TO HAVES

• Real ad budget spent in live auctions
• Large-scale ranking or recommendation systems
• Explaining tradeoffs to non-technical partners in plain terms
• Designing for auction feedback loops, selection bias and exploration
• Hands-on neural network work, such as embeddings of text, creative or user behavior
• AWS for data science: ECS, S3, Athena, SageMaker

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit‑sharing bonus, and competitive benefits. Launch Potato is a performance‑driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion.

We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.