Product Manager for Data Science

 

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products—Performance (affiliate), Creator (influencer), and Advocate (customer referral)—unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands, including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics, rely on impact.com to power more than 225,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We are looking for a Senior Product Manager (PM) to drive strategy and execution across our data science and AI ecosystem — from the machine learning platform and data foundations to applied ML and AI-powered products that deliver measurable business impact.

This is a pivotal role at the intersection of data science, machine learning engineering, and product strategy.  You’ll partner with data scientists, ML engineers, data engineers, and business leaders to define and deliver the capabilities that enable our teams to develop, deploy, and scale AI-driven insights and automation across the company.

What You'll Do:

ML Platform & Infrastructure

• Own the product vision and roadmap for our ML Platform, ensuring teams can easily experiment, train, deploy, and monitor models at scale.
• Partner with MLOps and Data Engineering to deliver shared components such as model registry, feature store, experiment tracking, and evaluation frameworks.
• Drive adoption of modern AI tooling (e.g., vector stores, LLM orchestration frameworks, GPU-based training environments).
• Define SLAs, performance metrics, and developer experience standards for the platform.

Data Strategy & Insights Enablement

• Lead the strategy for transforming raw data into structured, high-quality, and meaningful assets that power insight-driven product features such as competitive benchmarking, performance diagnostics, and opportunity identification.
• Define and evolve the data models, taxonomies, and semantic layers that make data consistent, interpretable, and ready for analysis.
• Partner with data science and engineering teams to ensure insights are accurate, contextual, and actionable, enabling teams and clients to make data-informed decisions confidently.

Applied ML & AI Use Cases

• Identify and prioritize high-value machine learning applications — such as recommendation systems, search relevance, anomaly detection, forecasting, and LLM-powered insights.
• Translate complex data science opportunities into productizable features with measurable outcomes.
• Collaborate with business and engineering teams to bring ML models into production — ensuring performance, interpretability, and ethical AI practices.
• Own success metrics (e.g., model ROI, adoption, latency, accuracy) and establish iteration loops with DS teams.

Strategy & Leadership

• Define the long-term strategy for AI/ML as a product capability — balancing foundational investments with applied innovation.
• Partner with senior leadership to align the ML roadmap with company priorities and data maturity.
• Champion best practices for experimentation, responsible AI, and data-driven decision making.
• Influence executive stakeholders through clear storytelling, value framing, and impact 

What You Bring:

• 6–10+ years of