Job Description

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:

• modeling user behavior (buyers and sellers)

• logistics (e.g. predicting delivery time)

• advertising campaigns (e.g. thematic recommendations)

• promotional pricing and sales campaigns 

• indicator forecasts at the level of the entire platform (e.g. demand for products)

What will your job involve?

• Building models that solve business problems - predictive, segmentation, forecasting, recommendation

• Using a wide range of model types, including boosting models, Bayesian methods, causal inference, optimization methods, deep learning

• Processing big data in GCP

• Working not only with tabular data, but also with spatial data, natural language texts, images and time series

• Taking part in implementations of off-line and on-line models

Why should you work with us?

• 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

• Thanks to the wide range of projects we carry out, you will never run out of interesting challenges

• 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

• You will have access to huge data sets and the latest data processing technologies

• 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

• 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:

• 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)

• Annual bonus up to 10% of the annual salary gross (depending on your annual assessment and the company's results)

• 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)

• English classes that we pay for related to the specific nature of your job

• 16" or 14" MacBook Pro with M1 processor and, 32GB RAM or a corresponding Dell with Windows (if you don’t like Macs) and other gadgets that you may need

• A high degree of autonomy in terms of organizing your team’s work; we encourage you to develop continuously and try out new things

• 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)

• If you want to learn more, check it out

Our offer is addressed to people who:

• Graduated with a degree strongly related to statistical/mathematical modeling, such as Mathematics, Physics, Economics, Computer Science or similar major

• Have at least 2 years of experience in data analysis using SQL and building machine learning solutions

• Want to translate business challenges into ML problems

• Can clearly communicate with business units - from formulating an analytical problem to a clear and intuitive presentation of results

• Program in Python and efficiently use basic development tools

• 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)