Hello, let’s meet! Who We Are While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started. What We Do We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data-driven solutions, and next-gen apps using ML, LLMs, and Generative AI. Our clients include Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, and Allegro or InPost. We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland! Beyond Projects What makes Xebia special? Our community. We run events like the Data&AI Warsaw Summit, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow. What sets us apart?  Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself. About Project The project focuses on developing intelligent decision-making mechanisms for a large-scale auction and bidding platform. By combining predictive signals, system data, and AI-driven approaches, the system supports and optimizes business decisions across the ecosystem. You will be: - designing and developing bidding and optimization strategies for CPC-based auction systems, including advanced objectives such as target ROAS, - optimizing auction mechanisms (ranking, pricing, filtering) to balance platform revenue, advertiser value, and marketplace stability, - building and maintaining offline simulation environments, including counterfactual simulations and auction replay systems, to safely evaluate algorithmic changes, - designing and implementing feedback loops and control mechanisms to ensure stable and robust system behavior under dynamic market conditions, - conducting advanced ecosystem-level analytics on large-scale datasets to identify nonlinear effects, equilibrium points, and systemic risks, - designing, executing, and analyzing complex experiments and causal inference studies, accounting for network effects and long-term system impact, - contributing to the evolution toward smart, autonomous bidding and auction optimization through data-driven initiatives and roadmap development. Your profile: - proficiency in Python and SQL, with experience working on large-scale datasets, data analysis, statistical modeling, and algorithm prototyping, - experience working with Big Data environments or distributed data processing systems, - strong quantitative background in Mathematics, Statistics, Data Science, Optimization, Decision Science, or Operations Research, - solid understanding of optimization theory, including linear, nonlinear, constrained, and stochastic optimization, - knowledge of game theory and market mechanisms, particularly in competitive or auction-based environments, - experience designing and implementing algorithms under multiple objectives and constraints, considering ecosystem-wide impact, - strong analytical and system-level thinking, with the ability to reason about feedback loops, system dynamics, and equilibrium behavior and translate business goals into quantitative solutions, - ability to collaborate effectively in cross-functional, international teams and very good command of English (spoken and written). Work from the European Union region and a work permit are required. Nice to have: - experience with auction systems, bidding strategies, or advertising technology, - familiarity with control theory concepts, such as PID controllers or similar feedback mechanisms, - exposure to causal inference, experimentation platforms, or advanced A/B testing setups, - background in economics, mechanism design, marketplace optimization, or experience working with large-scale decision systems. Recruitment Process CV review – HR call – Technical Interview – Client Interview I – Client Interview II – Hiring Manager Interview – Decision

Hello, let’s meet! Who We Are While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started. What We Do We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data and AI solutions, and cutting-edge applications to shape the future of tech. Our clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland! Beyond Projects What makes Xebia special? Our community. We support tech communities, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow. What sets us apart? Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself. You will be: - analysing large scale search, booking, and behavioural datasets to identify patterns impacting conversion, margin, and user relevance, - designing, training, validating, and iterating machine learning models for ranking and recommendation use cases, - developing margin aware, conversion aware, and relevance based scoring models aligned with defined business KPIs, - experimenting with semantic relevance and embedding based approaches for intent driven search, - defining features, evaluating data quality, and collaborating on feature readiness for ML training, - runing and interpreting offline evaluations and online experiments, including A B testing and shadow mode validation, - monitoring model performance, data drift, and retraining needs in production, - collaborating closely with data engineers and platform engineers to productionise models and ensure scalability, - documenting assumptions, results, and trade offs to support knowledge transfer and long term maintainability. Your profile: - ready to join within 2 weeks, - strong experience in applied data science and machine learning on real world datasets, - solid understanding of ranking, optimisation, or recommendation problems, - experience working with transactional and behavioural data, - proficiency in Python for data analysis and model development, - experience with experimentation, validation, and performance measurement of ML models, - understanding of overfitting, bias, and model generalisation, - ability to work closely with engineers to deploy models into production environments, - practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery, - exposure to Snowflake based analytics or ML workflows. Work from the European Union region and a work permit are required. Nice to have: - experience working in environments with business KPI guardrails such as margin, conversion, or NPS, - experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work. Recruitment Process: CV review – HR call – Interview – Client Interview – Decision

Hello, let’s meet! Who We Are While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started. What We Do We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data-driven solutions, and next-gen apps using ML, LLMs, and Generative AI. Our clients include Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, and Allegro or InPost. We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland! Beyond Projects What makes Xebia special? Our community. We run events like the Data&AI Warsaw Summit, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow. What sets us apart?  Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself. You will be: - architecting and implementing machine learning models for campaign optimization, focusing on bid strategies, budget allocation, and pacing algorithms within the DSP environment for pogrammatic campaigns with focus on CTV, - leading the design of the model orchestration layer to solve complex multi-objective optimization challenges, - working at the intersection of Product and Engineering, ensuring the model suite operates in sync to maximize performance across conflicting business KPIs, - driving data and ML strategy for audience segmentation and targeting capabilities, utilizing first- and third-party data sources to enhance product performance and advertiser outcomes, - collaborating closely with Product and Engineering teams to integrate new models and data pipelines into production systems, ensuring scalability and performance, - conducting deep-dive analytics to uncover strategic insights into campaign performance, market trends, and audience behavior, translating findings into actionable product recommendations, - serving as a subject matter expert in ad-tech data science for internal and external stakeholders, presenting complex methodologies and results clearly, - mentoring junior data scientists and contributing to the team’s culture of rigorous experimentation, statistical excellence, and innovative problem-solving. Your profile: - Master’s or Ph.D. Degree in Computer Science, Statistics, Economics, or a hard science field preferred, - 7+ years of professional experience in a Data Scientist role, with a significant focus on the advertising technology (ad-tech) space, - deep, demonstrable expertise in DSPs, programmatic advertising, and CTV measurement, - proven track record in developing and deploying models for bidder optimization and attribution/measurement, - fluent in advanced statistical and machine learning techniques, with a strong command of Python and SQL., - upper-intermediate English (B2+), - strong communication skills, with the ability to articulate technical concepts and complex model results to non-technical stakeholders. Work from the European Union region and a work permit are required. Candidates must have an active VAT status in the EU VIES registry: https://ec.europa.eu/taxation_customs/vies/ Nice to have: - experience with GCP and the Vertex AI ecosystem, as well as other tools such as feature stores and experiment tracking, - experience with LLMs and agentic AI frameworks/solutions, with special focus on evaluation. Recruitment Process CV review – HR call – Technical Interview – Client Interview – Hiring Manager Interview – Decision

Hello, let’s meet! Who We Are While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started. What We Do We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data and AI solutions, and cutting-edge applications to shape the future of tech. Our clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland! Beyond Projects What makes Xebia special? Our community. We support tech communities, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow. What sets us apart? Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself. You will be: - designing and developing statistical models for property price adjustments across time, location, quality, and condition, - building spatial algorithms (adaptive heatmaps, geographic clustering, polygon-based property search) to capture local market dynamics, - implementing comparable property recommendation with feature engineering across different property types, - developing market analysis pipelines with solid diagnostics: trend fitting, outlier detection, goodness-of-fit metrics, - integrating LLM-based classification services for document and property analysis, - exposing model outputs through production API endpoints and working with frontend engineers on data contracts, - debugging models in production: edge cases, numerical issues, data quality problems. Your profile: - solid statistics background: regression, GAMs, mixed/random effects, link functions, robust estimation, outlier handling, - proficiency in Python and the data science stack: NumPy, Pandas, statsmodels, SciPy, scikit-learn, - experience building and maintaining production APIs with FastAPI and Pydantic, - comfortable working with PostgreSQL and SQLAlchemy, - familiar with containerized environments (Docker, Kubernetes, GCP), - able to turn domain requirements into quantitative solutions and communicate trade-offs, - good command of English (spoken and written), - familiarity with basic statistical concepts (e.g., Bayes’ rule, linear regression, maximum likelihood estimation. Work from the European Union region and a work permit are required. Nice to have: - geospatial data and libraries (GeoPandas, Shapely, H3, GeoAlchemy2), - GAM libraries (PyGAM), JAX, or TensorFlow Probability, - task queues and async workflows (Celery, Redis), - observability tooling (OpenTelemetry), - ML pipeline frameworks (Kedro), - data validation and property-based testing (Pandera, Hypothesis, TestContainers), - R integration (rpy2), - LLM integrations (Google Gemini or similar), - frontend awareness (React, TypeScript), - real estate data, valuation methodology, or appraisal workflows. Recruitment Process: CV review – HR call – Interview – Client Interview – Decision