Job Description:
14 200 - 20 200 PLN in gross terms
In the Consumer domain, we create and maintain customer-facing applications that help millions of clients each day to complete their purchases. We are looking for a mid-level Data Scientist to join our team and help move our search engine beyond simple keyword matching toward a Domain-Aware Hybrid Search (integrating LLMs, Semantic Search, and Knowledge Graphs). In this role, you will be responsible for supporting the development of the Central Query Understanding mechanism and implementing Predictive & Assistive Discovery to reduce the "cost of search" through automated intent recognition.
This is the right job for you if:
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Have a degree strongly related to statistical/mathematical modeling.
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Possess at least 2 years of experience in data analysis and building machine learning solutions that have been released to production.
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Have a strong understanding of statistical and machine learning methods, specifically for forecasting and decision tree-based algorithms.
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Are proficient in Python and efficient in using basic development tools.
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Can process massive datasets (terabytes of data) using Google Cloud Platform solutions, working with tabular, spatial, natural language, image, and time-series data.
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Know English at a B2 level and Polish at a C1 level.
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Demonstrate core competencies in Analytical Thinking, Learning Agility, Cooperation, and Continuous Improvement & Innovation.
In your daily work, you will handle the following tasks:
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Designing, developing, and deploying models that solve complex business problems, including predictive, segmentation, forecasting, and recommendation models.
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Developing query-to-category and query-to-product matching models to enhance the search experience.
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Building internal AI Engineering competence, including fine-tuning small, efficient models.
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Taking an active part in all Data Science project phases: from problem formulation and data exploration to modeling, automation, release, and monitoring.
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Using a wide range of model types, including boosting, Bayesian methods, causal inference, optimization methods, deep learning, and forecasting models.
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Collaborating across teams, partnering with business stakeholders, analytics, and data engineering teams on experiment setup and deployment.
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Ensuring models reflect business processes' specificity and staying up-to-date with GenAI challenges.
What's in it for you:
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Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work.
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Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms).
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A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories.
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A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers).
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English classes that we pay for related to the specific nature of your job.
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A training budget, inter-team tourism ( see more here ), hackathons, and an internal learning platform where you will find multiple trainings.
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An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal.
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Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy.
And that's just the beginning! You can read more about the benefits here .
#goodtobehere means that:
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**You will join a team you can count on **- we work with top-class specialists who have knowledge- and experience-sharing in their DNA.
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You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create.
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You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job.
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You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support).
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You will create solutions that will be used (and loved!) by your friends, family and millions of our customers.
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You will meet the Allegro Scale, which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning.
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You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (it's been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about!
Send us your CV and… see you at Allegro!