About this role
If you are looking for a career at a dynamic company with a people‑first mindset and a deep culture of growth and autonomy, ACV is the right place for you. Competitive compensation packages and learning and development opportunities help you advance to the next level in your career. ACV invests in people and technology to help customers succeed.
Hybrid work environment based in Buffalo, NY or Toronto, CA.
About the Company
ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry with user‑designed, data‑driven applications and solutions to build the most trusted and efficient digital marketplace.
Benefits
Multiple medical plans including a high deductible, low cost health plan
Company‑sponsored (paid) Short‑Term Disability, Long‑Term Disability, and Life Insurance
Optional advantages such as Dental, Vision, Supplemental Life/AD&D, Legal/ID Protection, and Accident and Critical Illness Insurance
Generous paid time off including uncapped vacation days, paid sick days, 6 paid company holidays, 2 floating holidays, parental leave, bereavement leave, jury duty leave, voting leave, and other forms of paid leave as required by law
Employee Stock Purchase Program and opportunities to earn stock in the Company
Retirement planning through the Company’s 401(k)
Role Overview
We’re hiring a Product Manager to lead our Data & Search platform, focusing on leveraging industry‑leading data capabilities to improve how buyers discover inventory and how sellers maximize performance.
This role sits at the intersection of Auto Tech / Automotive Marketplace dynamics (supply, demand, pricing), Search & ranking systems, Data products (vehicle intelligence, enrichment), and Machine learning models (ranking, pricing, recommendations). It directly impacts conversion, liquidity, and revenue optimization across the platform.
Key Responsibilities
Own data products powering ML models, such as vehicle attributes, condition, and history.
Serve as connective tissue between Engineering, Data Science, ML teams, and Commercial stakeholders.
Collaborate with engineering and data science teams on ML model feature definition and selection, ensuring inputs align with product goals, customer behavior, and measurable business outcomes.
Define, evaluate, and improve model performance metrics aligned to product outcomes and customer value.
Employ a hypothesis‑driven approach to product development, converting ambiguity and assumptions into a clear framework for experimentation and validation via A/B testing and evaluating offline versus online metrics.
Ensure data quality, coverage, and reliability of underlying models and services that power critical product experiences and business decisions.
Translate complex data from multiple sources into actionable insights that drive product prioritization and innovation.
Improve inventory liquidity and pricing accuracy to drive trust and optimize the marketplace.
Identify high‑leverage product opportunities through ranking improvements, data enrichment, and better use of signals to improve relevance, conversion, and customer outcomes.
Guide product strategy by evaluating and communicating trade‑offs between technical implementation and business value (e.g., performance vs. explainability).
Define and own a 6–12 month roadmap across Data, Search, and ML‑driven features.
Articulate and advocate for product strategy, roadmap, and business outcomes to executive leadership to secure buy‑in and alignment.
Qualifications
4+ years of industry (Auto‑tech) product management experience.
Experience owning data‑heavy or technically complex product areas, including data pipelines, schema and event design, platform integrations, and prioritizing product investments that improve data accessibility, usability, and business impact.
Strong understanding of modern data hygiene practices, including data quality management, governance, lineage, validation, and the processes required to ensure trusted, reliable, and scalable data assets.
Demonstrated success in identifying and implementing LLM‑based solutions to augment user workflows.
Proven track record of leading end‑to‑end delivery of complex, technical products, driving measurable business impact.
Strong quantitative toolkit including SQL proficiency, rigorous experimentation design, and understanding of metrics architecture.
Experience working cross‑functionally with engineering teams and Agile release planning prioritization skills.
Presentation skills – ability to simplify complex data and technical systems.
Mentoring and coaching skills.
Bachelor’s degree in a relevant field (Computer Science, Engineering, Data Science,