Senior Product Manager - Technical

Compact Information Systems LLC•Kirkland, WA

14h•$155,000 - $185,000•Onsite

About The Position

Deep Sync is seeking a Senior Product Manager - Technical to own the product surface for audience selection, purchase, and delivery into marketing channels. This role involves new product development, taking ideas from hypothesis to paid offerings, and discontinuing underperforming products. The position requires a strong understanding of AI and its application in marketing technology, with a focus on building products that serve machines as readily as people. The company operates with a flat organization and a fast product development cadence, based in Kirkland, WA.

Requirements

AdTech or MarTech product experience, including building and releasing products in audience data, DSP/SSP, CDP, identity/onboarding, clean rooms, or measurement.
Understanding of identity data, both online and offline, including deterministic and probabilistic matching, first-party data onboarding, and the impact of privacy regulations.
Exposure to or demonstrated understanding of both consumer and business marketing.
Sound judgment and the ability to make decisions quickly with incomplete information, assessing trade-offs and explaining reasoning.
Experience taking a product from proposal to paying customer, including testing before building.
Data fluency, including strong SQL skills, familiarity with Snowflake, Databricks, or S3/Parquet data lakes, and the ability to validate data coverage and match rates.
AI fluency, including practical use of current AI tools for analysis, prototyping, and writing.
Ability to judge where AI models or agents fit within a product and how their output is evaluated.
Written clarity with plain sentences, stated positions, and visible reasoning.
A record of stopping work on features, roadmap items, or projects, and the ability to describe the cost and decision-making process.
Experience with distributed working environments, particularly with teams in India, and success in written collaboration.
At least four years in product management, with at least three years in AdTech, MarTech, or a data-as-a-service business.
Experience selling software or data to other businesses serving consumer and business marketing.
A track record of releasing products into existing customer platforms and starting new initiatives from scratch.
Practical use of machine learning or generative AI in product releases or daily work.
Bachelor's degree or equivalent practical experience.

Nice To Haves

Direct mail or other offline channels experience.
Experience with data distributed through Snowflake or Databricks marketplaces.
Experience with clean rooms.
Experience in a company built by acquisition.

Responsibilities

Own an area of the product from problem identification through to outcome, including the business case, requirements, and post-release usage.
Develop requirements documents that clearly state the problem, decision, scope, and success metrics.
Establish product usage, make the case for retiring unused features, and maintain scope discipline.
Manage releases by selecting early customers, defining test criteria, and reporting results.
Identify new product opportunities, such as untapped audiences or unaddressed customer needs.
Conduct early validation with a small number of customers, with pre-agreed metrics and short written findings.
Determine the appropriate application of AI models or agents within the product, specify output evaluation, and demonstrate ideas with working prototypes.
Design products for consumption by machines, ensuring predictable interfaces, described data, and actionable output.
Manage product progression or discontinuation based on performance and investment justification.
Engage with sales, delivery, and client-facing teams to gather market insights.
Understand the distinct needs and measurement criteria for both consumer and business marketing.
Align with product marketing on revenue generation, identifying which audiences and attributes are most valuable.
Determine the value and maintenance requirements for integrations with platforms like The Trade Desk, DV360, Meta, Amazon, TikTok, LiveRamp, Snowflake, and Databricks marketplaces.
Verify data quality, including match rates, coverage by attribute, record counts, and source costs against attributed revenue, using SQL.
Collaborate with data owners for identity resolution, attribute taxonomy, and modeling, specifying market requirements.