Early Career: Associate Data Science Product Manager - NYC

This role is not open to visa sponsorship or transfer of visa sponsorship including those on OPT and STEM-EXT OPT, nor is it available to work corp-to-corp.

Red Ventures Home empowers partners through a unique blend of high-scale proprietary distribution, data models, AI-enabled applications, and strategic client partnerships. We help our clients unlock significant and sustainable growth across the home services ecosystem, ranging from telecom and security to energy and home automation.

We are looking to hire Associate Data Science Product Managers to join our Home Client Services division. This product team is responsible for transforming organizations’ customer acquisition, retention and business operations through applications in AI & ML. In this role, you’ll help tailor, optimize, and scale data science solutions to solve specific partner and customer challenges, ensuring our technology delivers measurable value in the marketplace.

An example project includes building and deploying real-time technology, powered by generative AI, to assist our sales professionals.

We believe successful Data Science Product Managers have a wide set of experiences and skill sets in the data domain. This hybrid position offers you hands‑on opportunities in data science, data analysis, and product management. In your first two years, you’ll get repetitions in contributing to product life cycles via product analytics, roadmap support, model building, and influential communication with product leadership.

Curious how Home fits into Red Ventures? .

As an Associate Data Science Product Manager, you will play a pivotal role in bridging the gap between complex data science initiatives and impactful product solutions to create value for both our business and our customers.

• Responsible for identifying opportunities to increase the impact of your product through deep understanding of the problem space, thorough comprehension of the product strategy and technology, and advanced statistical analysis. Effectively communicating recommendations to your product leads to create buy‑in and action.
• Translate your recommendations into clear work streams and features that contribute to the product roadmap. Collaborate with Data Science, Design, and Engineering teams to turn objectives into detailed requirements with assistance from your product lead.
• Leverage algorithms and programming tools to execute relevant technical work streams. This includes building items such as:
  • Data pipelines to gather, manipulate, prepare, and visualize large datasets
  • Machine learning models for offline and proof‑of‑concept use cases
  • Agentic workflows to automate tasks or provide reasoning capabilities for specific features in your product
• End to end ownership of experiments. Assist in deploying features aimed at improving core KPIs. Conduct analyses to assess the impact of the experiments, synthesizing and owning the narrative.
• Promote adoption and usage of your product and tooling. Interact directly with end‑users for training, feedback, and user testing.
• Stay up‑to‑date with advancements in machine learning and generative AI to identify innovative ways to solve business challenges.

• Strong analytical and critical thinking skills. Can connect the dots between the business problem, the approach, the data, and the relevant recommendation.
• Strong grit and learning mentality when faced with challenging projects, unfamiliar technology, and ambiguous business problems. Takes a proactive approach to overcoming obstacles.
• Creative problem solver with an entrepreneurial mindset and a strong business acumen with an interest in solving business and customer problems to create impact.
• Showcases high EQ - can collaborate effectively in a team environment.

• Graduating with a bachelor’s or master’s degree in Summer 2026, with academic and/or practical experience in fields such as computer science, data science, statistics, or product management.
• Demonstrated ability to collect, mine, and manipulate large data from disparate data sources, with an ability to dig deep and understand the process (e.g., SQL, Pandas, Tableau).
• Hands‑on…