Data Science Product Manager, Yield Optimization at Trellis

, , -

Full Time

Start Date

Immediate

Expiry Date

15 Mar, 26

Salary

0.0

Posted On

16 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Predictive Models, Full-Stack Data Proficiency, Recommendation Systems, Ad Tech, Yield Optimization, SQL, Business Acumen, Product Acumen, Communication, High Autonomy, Execution, Model Accuracy, Marketplace Optimization, External Partnerships, Model Development

Industry

Software Development

Description

Trellis is a profitable, fast-growing Series A startup backed by General Catalyst, QED, NYCA, and Amex Ventures. We’re reimagining how people shop for home and auto insurance, using smart technology to make something historically painful feel refreshingly easy. Every day, we help people save time, money, and unnecessary headaches. Behind the scenes, our fully remote team moves fast, owns their craft, and builds products that genuinely make life better. Led by a three-time fintech founder with a proven track record of going big, we’re building something special, and we’re just getting started. If you’re hungry to make an impact and love solving complex problems with a scrappy crew, you’ll love it here. Your Mission We are seeking a Data Science Product Manager, Yield Optimization to lead the development, implementation, and ongoing improvement of predictive models that are central to our marketplace and revenue generation by ensuring that we show the optimal offers to our users. This critical role is focused on continuously improving decision-making for every individual user—from the moment they arrive to their final placement with an insurance provider—directly impacting funnel optimization and our revenue engine. This is a highly cross-functional role where you will collaborate closely with internal Engineering and business stakeholders to turn messy, real-world data into clear insights and working models, while also interfacing externally with our ad and call buyers. Success requires a blend of product ownership, business acumen, and full-stack data science proficiency to define problems, prioritize opportunities, and ensure the models you own drive maximum business impact. This is a fully remote position, based in the US or Canada, and will report directly into Keith Schreer, VP of Data. What You'll Do: Lead Product & Planning: Partner with Engineering and Business teams to seamlessly integrate models into our recommendation engine. Own Predictive Model Roadmap: Drive the full lifecycle of our yield optimization models, from ideation and development to production monitoring and iteration. Drive Revenue: Continuously evaluate and improve model accuracy and interpretability to directly impact key business KPIs like revenue and conversion rates. Cultivate a Thriving Marketplace: Use sophisticated models to intelligently match users to the best offers, driving value for our internal agency and external buyers. Drive External Partnership Success: Interface directly with external partners, ensuring mutual success and aligning model performance with partner goals. What You'll Need to Succeed: 7+ years of experience in Data Science roles implementing predictive models. Proven Full-Stack Data Proficiency: end-to-end ownership of predictive models used in production. Experience with recommendation systems, ad tech, or yield optimization models. Expert proficiency in SQL and the ability to independently source, wrangle, and understand data across the full stack. Business & Product Acumen: Strong ability to translate complex business problems (like optimizing revenue) into clear analytical questions and communicate insights/tradeoffs to non-technical stakeholders and external partners. High Autonomy & Execution: Demonstrated capacity to operate with high autonomy, follow through on unowned problems, and thrive in a fast-paced, scrappy startup environment. Communication: Clear, concise, and professional written and verbal communication for both internal alignment and external partner management. Preferred: Experience with ML platforms (e.g., DataRobot) or a background in Ad Tech/Insurtech is a plus. Why Trellis? Because life’s too short for boring jobs. We’re a team of builders, dreamers, and doers reshaping an industry that touches every household in America. At Trellis, you’ll have real ownership, meaningful impact, and the chance to grow alongside a company that’s scaling fast. Here’s what makes Trellis an incredible place to build your career: ✨ A flat, transparent culture where your voice actually matters 🚀 Ground-floor opportunity with room to stretch and grow 💰 Compensation at the 75th+ percentile 🏡 100% remote... work from wherever you do your best thinking (In the US or Canada, that is) 🎉 Quarterly team events that keep our fully remote culture connected and fun And yes, the perks are pretty great too: 🌴 Flexible vacation (seriously, we want you to take it) 🩺 100% employer-paid health insurance for employees (65% for dependents) 💻 Home office budget to set up your perfect workspace 🧘🏼‍♂️ Wellness events throughout the year, because we believe in investing in the full human, not just the employee 💸 Automatic 401(k) contribution, FSAs, bonuses, and equity opportunities to invest in your future 🐣 Paid parental leave 👉 If you’re looking for a place where you can do the best work of your career, while building something that actually matters, we’d love to meet you.

Responsibilities

Lead the development and improvement of predictive models for yield optimization, impacting user decision-making and revenue generation. Collaborate with engineering and business teams to integrate models into the recommendation engine and drive revenue through model accuracy.