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Lead Data Scientist, AdTech
Launch PotatoCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing models for auto insurance carrier matching, focusing on conversion metrics and media spend management. Proficient in end-to-end model ownership, including deployment and monitoring, with a strong foundation in Python and SQL.
Highest-signal resume keywords
Applied Data ScienceModel Deployment and MonitoringPython ExpertiseSQL ExpertiseMedia Buying Optimization
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Build models deciding which auto insurance carrier each shopper sees on the click wall
- Optimize user-to-carrier matching for conversion and carrier bidding
- Own buying models behind media spend and hold them to ROAS
- Put carrier conversion data, including quotes, policies and acquisition cost, into production models
- Frame problems with the business and find, build and validate models
- Take models through deployment and monitoring
- Run insurance marketplace media buying independently by day 60
- Deliver click-wall matching, production conversion models, scalable automated bidding, approaches for repeat users and sparse sessions, and models resilient to drift and changing objectives
- Collaborate with an ML engineer on production implementation
- Expand scope from auto insurance to other verticals over time
Requirements
What you’ll need- 5+ years of hands-on applied data science with measurable business impact
- Models drove paid media decisions: spend, bidding or ad serving; attribution and reporting alone do not qualify
- Ability to explain work down to the loss function and architecture choice, including neural network fundamentals
- Experience handling late labels, sparse features or drift
- Ability to own models end to end, from finding data through deployment and monitoring
- Expert Python and SQL
- Real ad budget spent in live auctions (nice to have)
- Large-scale ranking or recommendation systems (nice to have)
- Explaining tradeoffs to non-technical partners (nice to have)
- Designing for auction feedback loops, selection bias and exploration (nice to have)
- Hands-on neural network work (nice to have)
- AWS for data science: ECS, S3, Athena, SageMaker (nice to have)
- CI/CD deployment (nice to have)
Benefits
Comp & perks- Profit-sharing bonus
- Competitive benefits
- Remote-first work arrangement
- Diverse, inclusive team and culture
- Equal Employment Opportunity company
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Model BuildingUser-to-Carrier MatchingConversion OptimizationNeural Network FundamentalsHandling Late LabelsSparse Features ManagementLarge-Scale Ranking SystemsRecommendation SystemsCI/CD Deployment
Soft Skills
Problem FramingCollaboration with EngineersExplaining Technical Concepts
Tools & Technologies
AWSECSS3AthenaSageMaker
Industry Keywords
Auto InsuranceMedia SpendROASAttributionAd ServingAuction Feedback Loops