Machine Learning Product Manager

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MidHybryda·WarszawaFull-time

#469694·Dodano 7 dni temu·0

Źródło: jobs.techtree.dev

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Tech Stack / Keywords

Machine LearningProduct ManagementReal-Time BiddingAd TechProgrammaticA/B TestingStatisticsP&L ManagementData Science LeadershipDSPSSP

Podsumowanie oferty

Own the product roadmap and financial results for a machine-learning-driven real-time bidding system that prices ad impressions across the group’s properties and external inventory. Lead the data science team and guide bidding models for performance campaigns, on a system handling millions of auctions per minute.

Wymagania

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.

Obowiązki

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.
Build an edge: Track the programmatic market, new ad formats and industry standards to strengthen competitive advantage.

Benefity

Responsibility for one of the group’s key advertising products, with real impact on financial results.
Work with a mature data science and engineering team on a system handling millions of auctions per minute.

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