or apply directly on LP Careers Page's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 80 days LP Careers Page's roles stay open a median of 80 days
- Reposted
- No
- Salary listed
- No 0% of LP Careers Page's roles list one
- Ghost-job risk at LP Careers Page
- high 12 stale, 0 reposted of 15 open
- Hiring momentum
- 18 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-22
Measured from postings appearing on and disappearing from LP Careers Page's own greenhouse board since 2026-08-03. Full hiring picture for LP Careers Page.
About this role
In this role, you will build and manage models that optimize the auto insurance marketplace by determining which carriers to present to shoppers based on conversion likelihood. You will be responsible for end-to-end model development, from data sourcing to deployment and monitoring, working closely with an ML engineer. Initially focused on auto insurance, the scope may expand to other verticals over time, with success metrics tied to media buying and model performance.
- benefits
- 2/5
- freshness
- 1/5
- career value
- 4/5
- role clarity
- 4/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of LP Careers Page as an employer.
What you need
- 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 have
- 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
What you get
- Base salary set according to market rates for the nearest major metro
- Profit-sharing bonus
- Competitive benefits
- Future increases based on company and personal performance, not annual cost of living adjustments
Worth weighing
- Remote work with most of the team on East Coast hours
- The role requires handling complex data issues like late labels and sparse features
- Success metrics are heavily tied to business outcomes, which may add pressure
Summarised from LP Careers Page's posting. Read the full original.
Listed by LP Careers Page on their greenhouse job board, last confirmed open on 2026-10-22. PitchMeAI is not the employer.
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