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TechTree

Machine Learning Product Manager

Warszawa
vor 4 Tagen

Kurzfassung

Machine Learning Product Manager for a digital media group. Owns ML-driven real-time bidding system, P&L, and roadmap. Manages data science team, oversees ML production quality, and reports to the Management Board. Requires 5+ years in ML product development (2+ in management), STEM degree, strong ML/stats understanding, P&L accountability, and English/Polish fluency.

Von KI erstellte Kurzfassung des Anzeigentextes.

The opportunity

Join one of Poland's largest digital media and technology groups and take product ownership of its machine-learning-driven real-time bidding system. The bidder prices every single ad impression in a fraction of a second for performance campaigns (ROAS, CPO, CPC, CPA) - across both the group's own properties and external inventory - handling millions of auctions per minute.

The role

As Machine Learning Product Manager, you'll connect the world of models with the bottom line. You'll own the product's P& L and roadmap, set development priorities, lead the data science team and co-author reporting for the Management Board.

What you'll do

  • Own the numbers: Take responsibility for the product's financial results (revenue, margin, client ROAS) and its roadmap.
  • Translate business into models: Turn business goals into measurable targets for bidding models and algorithms - calibration, margin, win rate, CPM.
  • Lead the team: Manage a team of data scientists - priorities, development and quality of work.
  • Keep ML healthy in production: Oversee the quality and stability of ML solutions in production - monitoring, incident response and root-cause analysis of performance drops.
  • Report to the top: Present results, risks and recommendations to the Management Board and key stakeholders (sales, SSP partners, engineering teams).
  • Align the ad stack: Work with the teams that co-build the group's advertising stack and agree priorities across them.
  • Track the programmatic market, new ad formats and industry standards.

What you bring

  • 5+ years of experience developing machine-learning-based products, including at least 2 years in a product or management role.
  • Experience managing a data science or ML team.
  • A university degree in a STEM field.
  • A solid understanding of machine learning: probabilistic classification models, metrics (AUC, log loss, calibration), data and feature drift, offline vs. online evaluation.
  • Strong statistics and experiment design skills: A/B testing and common interpretation pitfalls (mix effects, sampling, seasonality).
  • Experience owning a P& L or being accountable for business results.
  • Very good English (min. C1) and Polish.

Nice to have:

  • A PhD in a STEM field, especially data science, statistics, computer science or physics.
  • Experience with real-time bidding or ad tech: DSP, SSP, bid shading, floor pricing, pacing, conversion attribution.
  • Experience in an international environment, including study or work abroad.
  • Knowledge of production ML system architecture: feature stores, model serving.
  • Experience with performance campaigns (e-commerce, ROAS).

How you work:

  • You stay effective under time and revenue pressure, including during incidents that hit revenue.
  • You communicate complex technical topics clearly and with data, including in Board-level reports.
  • You think in margin, risk and ROI - not just model metrics.
  • You lead expert teams by building trust, giving feedback and developing people.
  • You think critically: you dig for root causes and test hypotheses.
  • You work effectively with many stakeholders and negotiate priorities.

What we offer

  • Ownership: Responsibility for one of the group's key advertising products, with real impact on financial results.
  • Scale: Work with a mature data science and engineering team on a system handling millions of auctions per minute.
  • Flexibility: Hybrid work from the Warsaw office.

Logistics

  • Location: Warsaw, hybrid.
  • Type: Full-time.

Recruitment process:

The process includes an introductory conversation, an interview focused on your experience and role-related expertise, and a discussion of the role and next steps.

Veröffentlicht 2026-10-29
Läuft ab 2027-01-27
Quelle