Data Scientist @ Webinterpret Poland Sp. z o.o. in Webinterpret Poland Sp. z o.o.

Webinterpret is a tech company acting globally to help brands and retailers conquer new markets successfully via online marketplaces. Our end-to-end cross-border solution is the key to make your product reach and convert international buyers affordably via our automated localization services, multi-language SEO & SEM and logistics. Since 2007, we have helped over 40,000 companies worldwide and generated over 300 m€ of sales. Data Scientist Work framework :Scrum Location :100% Remote or Warsaw (city center) Experience :Mid-Senior Flexible working hours :Yes (with a start time between 8.00 AM - 10.00 AM CET/CEST) Requirements : At least 3 years of commercial experience Experience in: Python Data analysis and machine learning Data processing (and SQL databases) Good understanding of statistics and probability Up-to-date knowledge of machine learning models and current trends Interest in data pipelines and software development Good written and spoken English (comfortable with working in an international environment) Technology stack: Development Python development (e.g. dataclasses, flask, faust, Kedro) SQL (Athena, Postgresql, Redshift), NoSQL (Redis, Mongo) Infrastructure and data pipelines (Kafka, RabbitMQ, AWS, Docker, Kubernetes, MLflow, Kubeflow, Kserve) Experiments Machine learning (sklearn, Tensorfow, pyTorch, spaCy, flair) LLMs (langchain) Analysis Python data processing (e.g. pandas, numpy, Kedro) Statistical analysis (scipy, statsmodels, Prophet, CausalImpact, pyMC) Who are we and who are we looking for? As a part of Webinterpret, our team is focusing on creating data-driven (using machine learning, statistics, and heuristics approaches) solutions to optimize and enhance various services that support international sales for hundreds of millions of products in 15+ different countries. On a daily basis, we deal with tasks such as product classification, product localization, shipping cost estimation, advertising optimization, price optimization, and many more. Our day-to-day tasks can be classified into one of three categories: development, experiments, and analysis. We are looking for a Data Scientist who will be able to work in all of those fields. Development Since all of our systems are processing millions of products every day, we try to develop our services in a scalable and efficient way. This means when building our system, we care for high code quality, test coverage, data processing automation, and low latency to optimize their performance and generated costs. Experiments On the other hand, it’s important to think about potential growth, that’s why we are also working on optimizing the business value of existing products and looking for new business opportunities. This means we often try to build new ML-based and (and recently also LLM-based) products and validate their potential in the real, production environment. Analysis Since we have access to terabytes of historical e-commerce data, we are leveraging it to improve the business performance of our products. This means we are often preparing in-depth exploratory and statistical analyses to find hidden patterns and trends, as well as analyzing results and confirming the significance of our experiments. We offer "WI" won't reveal much about ourlegendary company parties; they are far from being "casual" or "boring" drinks. Language lessons. Company Revenue Sharing scheme "LTIP" - the more the company grows, the more you receive from it. At least 3 years of commercial experience, Experience in: Python Data analysis and machine learning Data processing (and SQL databases), Good understanding of statistics and probability, Up-to-date knowledge of machine learning models and current trends, Interest in data pipelines and software development, Good written and spoken English (comfortable with working in an international environment). Webinterpret is a tech company acting globally to help brands and retailers conquer new markets successfully via online marketplaces. Our end-to-end cross-border solution is the key to make your product reach and convert international buyers affordably via our automated localization services, multi-language SEO & SEM and logistics. Since 2007, we have helped over 40,000 companies worldwide and generated over 300 m€ of sales. Data Scientist Work framework :Scrum Location :100% Remote or Warsaw (city center) Experience :Mid-Senior Flexible working hours :Yes (with a start time between 8.00 AM - 10.00 AM CET/CEST) Requirements : At least 3 years of commercial experience Experience in: Python Data analysis and machine learning Data processing (and SQL databases) Good understanding of statistics and probability Up-to-date knowledge of machine learning models and current trends Interest in data pipelines and software development Good written and spoken English (comfortable with working in an international environment) Technology stack: Development Python development (e.g. dataclasses, flask, faust, Kedro) SQL (Athena, Postgresql, Redshift), NoSQL (Redis, Mongo) Infrastructure and data pipelines (Kafka, RabbitMQ, AWS, Docker, Kubernetes, MLflow, Kubeflow, Kserve) Experiments Machine learning (sklearn, Tensorfow, pyTorch, spaCy, flair) LLMs (langchain) Analysis Python data processing (e.g. pandas, numpy, Kedro) Statistical analysis (scipy, statsmodels, Prophet, CausalImpact, pyMC) Who are we and who are we looking for? As a part of Webinterpret, our team is focusing on creating data-driven (using machine learning, statistics, and heuristics approaches) solutions to optimize and enhance various services that support international sales for hundreds of millions of products in 15+ different countries. On a daily basis, we deal with tasks such as product classification, product localization, shipping cost estimation, advertising optimization, price optimization, and many more. Our day-to-day tasks can be classified into one of three categories: development, experiments, and analysis. We are looking for a Data Scientist who will be able to work in all of those fields. Development Since all of our systems are processing millions of products every day, we try to develop our services in a scalable and efficient way. This means when building our system, we care for high code quality, test coverage, data processing automation, and low latency to optimize their performance and generated costs. Experiments On the other hand, it’s important to think about potential growth, that’s why we are also working on optimizing the business value of existing products and looking for new business opportunities. This means we often try to build new ML-based and (and recently also LLM-based) products and validate their potential in the real, production environment. Analysis Since we have access to terabytes of historical e-commerce data, we are leveraging it to improve the business performance of our products. This means we are often preparing in-depth exploratory and statistical analyses to find hidden patterns and trends, as well as analyzing results and confirming the significance of our experiments. We offer "WI" won't reveal much about ourlegendary company parties; they are far from being "casual" or "boring" drinks. Language lessons. Company Revenue Sharing scheme "LTIP" - the more the company grows, the more you receive from it. ,[ Dealing with tasks such as product classification, product localization, shipping cost estimation, advertising optimization, price optimization, and many more., Our day-to-day tasks can be classified into one of three categories: development, experiments, and analysis. We are looking for a Data Scientist who will be able to work in all of those fields., Since all of our systems are processing millions of products every day, we try to develop our services in a scalable and efficient way. This means when building our system, we care for high code quality, test coverage, data processing automation, and low latency to optimize their performance and generated costs., On the other hand, it’s important to think about potential growth, that’s why we are also working on optimizing the business value of existing products and looking for new business opportunities. This means we often try to build new ML-based and (and recently also LLM-based) products and validate their potential in the real, production environment., Since we have access to terabytes of historical e-commerce data, we are leveraging it to improve the business performance of our products. This means we are often preparing in-depth exploratory and statistical analyses to find hidden patterns and trends, as well as analyzing results and confirming the significance of our experiments.] Requirements: Python, Data analysis, Machine learning, SQL Tools: Jira, Confluence, Agile, Scrum. Additionally: Sport subscription, Training budget, Private healthcare, Flat structure, Small teams, International projects, Integration events, Friendly atmosphere, Language classes, Sharing scheme program, Free coffee, Bike parking, Playroom, Free snacks, Free beverages, In-house trainings, Modern office, Startup atmosphere, No dress code, Free breakfast.