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WorkWave is seeking a Technical Product Manager (Data & AI) to shape the AI and data vision at the intersection of data science, engineering, and customer value. You will co‑develop predictive models and data products with executive clients and drive features that move SaaS metrics.
This remote-first role emphasizes translating complex problems into specs, partnering with GTM teams, and delivering high‑impact data experiences that accelerate ARR growth.
We aren’t just looking for someone to manage a backlog; we’re looking for the founding architect of our customer-facing data and AI strategy.
As a Technical Product Manager (Data & AI), you will sit at the high-impact intersection of cutting-edge Data Science, modern Engineering, and customer-facing value. This is a highly visible, strategic role where you’ll partner directly with executive-level clients to co‑develop the predictive models, analytical features, and SaaS data products that will define our industry.
If you want to move away from internal tooling and actually ship AI/ML features that drive massive, quantifiable ARR, this is your playground.
Own the Predictive Roadmap: Drive the vision and strategy for our external AI/ML models, advanced analytics features, and data products.
Co-Innovate with Clients: Embed deeply with strategic customers and design partners to validate ideas, uncover raw user needs, and co‑develop next‑gen features.
Tell the Story of Data: Partner with UX and Data Science to turn complex backend algorithms into beautiful, intuitive data visualizations and high‑impact product demos.
Translate Complexity: Act as the ultimate bridge. Translate messy customer business problems into precise technical specs, transformation logic, and data requirements for our engineers and data scientists.
Own the GTM: Collaborate with Product Marketing and Sales to launch features that aren’t just technically impressive, but actually move the needle on SaaS metrics (Adoption, Retention, ARR expansion).
Hypothesize & Validate: Use your analytical skills to dive into data assets, validate assumptions, and prove (or disprove) product hypotheses before writing code.
3+ years of relevant experience across Product Management, Data Analytics, or Data Engineering.
Strong Business & Product Acumen: The ability to look at a complex technical feature and immediately see how it connects to customer ROI.
SQL Fluency: You are comfortable writing joins and aggregations to explore data yourself. (We care about your analytical problem‑solving, not whether you memorized advanced syntax).
Data Visualization Chops: Experience with a modern BI platform (e.g., Sigma, Tableau, Looker) and a strong sense of how to present data clearly.
The “Translator” Superpower: Elite communication skills. You can pitch a vision to an executive client, align a sales team, and debate data modeling with an engineer.
3+ years of relevant experience across Product Management, Data Analytics, or Data Engineering.
Strong Business & Product Acumen: The ability to look at a complex technical feature and immediately see how it connects to customer ROI.
SQL Fluency: You are comfortable writing joins and aggregations to explore data yourself. (We care about your analytical problem‑solving, not whether you memorized advanced syntax).
Data Visualization Chops: Experience with a modern BI platform (e.g., Sigma, Tableau, Looker) and a strong sense of how to present data clearly.
The “Translator” Superpower: Elite communication skills. You can pitch a vision to an executive client, align a sales team, and debate data modeling with an engineer.
Our Stack: Experience with (or a burning desire to learn) our modern data stack: Snowflake, DBT, Fivetran, and Sigma.
Industry Context: Experience in complex B2B SaaS verticals- especially physical operations like Field Services (logistics, routing, dispatch) or Building Services is a massive plus. These industries are sitting on massive, unoptimized datasets ripe for AI disruption.
Coding Lite: Familiarity with Python or R for lightweight data analysis.
AI/ML Exposure: Experience working around the machine learning lifecycle or productionized models.
$155,000 - $160,000 a year
In our commitment to salary transparency, we provide a compensation range for each role.In addition to the base salary this role is bonus eligible, the final offer will be dependent on various factors, including the candidate’s qualifications, relevant experience, and the organization’s budget. Our Talent Acquisition team will provide more information about the compensation package for this position during the interview process.
Please note that salary estimates provided by websites (LinkedIn, Glassdoor, etc.) and not by WorkWave may not accurately reflect the actual salary range for the position.
_ We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, age, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status: ___Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At WorkWave, we are dedicated to building a diverse, inclusive and authentic workplace, so if you feel like you could make a great impact in this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may just be the right candidate for this or other roles!