Job Description
A hybrid work model requires 1 day a week in the office (Warsaw).
At Data Science Hub, we create solutions based on Data Science / Machine Learning for business teams at Allegro. Our daily work is characterized by diversity, both in terms of the topics analyzed and the modeling techniques and technologies used. It is a great place for people who expect opportunities for continuous development and a unique opportunity to gain multidisciplinary knowledge about the activities of eCommerce platforms. Our portfolio of projects included supporting domains such as:
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modeling user behavior (buyers and sellers)
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logistics (e.g. predicting delivery time)
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advertising campaigns (e.g. thematic recommendations)
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promotional pricing and sales campaigns
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indicator forecasts at the level of the entire platform (e.g. demand for products)
What will your job involve?
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Co-creating projects on each stage - from concept to productization - to deliver insights and models solving business problems from the area of DEX/CX/operations- predictive, segmentation, forecasting, recommendation etc.
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Using a wide range of model types, including boosting models, Bayesian methods, causal inference, optimization methods, deep learning
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Processing terabytes of data using Google Cloud Platform solutions
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Working not only with tabular data, but also with spatial data, natural language texts, images and time series
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Taking part in implementations of off-line and on-line models
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Provide technical leadership and mentorship to junior and mid-level data scientists
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Cooperation with other teams: business stake-holders, analytics, data engineers
Why should you work with us?
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Data Science plays a key role in the operation of Allegro - we are a data-driven technology company, and through the models and analyses provided you will have a significant impact on one of the largest eCommerce platforms in the world
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Thanks to the wide range of projects we carry out, you will never run out of interesting challenges
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Support of experienced Data Scientists - there is always someone to exchange ideas with, because we have the best specialists and experts in their field on board
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You will have access to huge data sets and the latest data processing technologies
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You will have the opportunity to learn the tools and technologies in practice:
Python, MLFlow, GCP BigQuery, Tableau, Composer, Dataflow, PySpark. -
You will learn good programming, engineering and code management practices
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We share our knowledge at industry conferences and trainings, we are an active participant and co-creator of the Data Science / Machine Learning community in Poland and in the world
What we offer:
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A hybrid work model that you will agree on with your leader and the team. We have well-located office (with fully equipped kitchens and bicycle parking facilities) and excellent working tools (height-adjustable desks, interactive conference rooms)
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Annual bonus up to 10% of the annual salary gross (depending on your annual assessment and the company's results)
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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 high degree of autonomy in terms of organizing your team’s work; we encourage you to develop continuously and try out new things
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Hackathons, team tourism, training budget and an internal educational platform, MindUp (including training courses on work organization, means of communications, motivation to work and various technologies and subject-matter issues)
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If you want to learn more, check it out
Our offer is addressed to people who:
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Graduated with a degree strongly related to statistical/mathematical modeling, such as Mathematics, Physics, Economics, Computer Science or similar major
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Have at least 2 years of experience in data analysis using SQL and building machine learning solutions
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Want to translate business challenges into ML problems
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Can clearly communicate with business units - from formulating an analytical problem to a clear and intuitive presentation of results
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Program in Python and efficiently use basic development tools
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Understand statistical and machine learning methods, especially ones used for forecasting and algorithms based on decision trees
This may also be of interest to you:
Allegro Tech Podcast → https://podcast.allegro.tech/
Send in your CV and see why it is #dobrzetubyć (#goodtobehere)
What We Do
Allegro is the most popular shopping platform in Poland and the largest e-commerce platform of European origin. We operate a marketplace model which means that customers can buy whatever they need from over 135,000 merchants, who can list an unlimited number of offers on our platform. We offer products in all key categories including Automotive, Fashion, Home&Garden, Electronics, Books and Collectibles, Kids or Health and Beauty. Each month, 22 million customers visit our platform, which is equivalent to almost 80% of all Internet users in Poland. They can choose from over 250m offers at the most attractive prices with maximum convenience including fast and free deliveries under the Allegro Smart! programme, modern financial services (Allegro Pay), as well as Poland’s widest 50k pickup points network. In 2019 we celebrated the 20th anniversary of Allegro in Poland. For over two decades, we have been serving consumers and promoting the idea of entrepreneurship in one of the most innovative areas of the economy. We have come a long way from an auction site for private individuals looking for a modern alternative to their local flea market. Today, we are a vibrant international marketplace platform for professional sellers and a must-have sales channel for top international brands and retailers. We currently employ more than 7000 employees and each of us ranks among the best experts in their field. Whether it’s in Technology, Customer Experience, Commerce, Delivery Experience or many other teams, we’re all proud to say that Allegro employs the best people on the market and all of us are ready to admit that it’s #goodtobehere.