Top Data Science Jobs in Warsaw
As a Data Science Engineer at Accuris, you will develop and maintain data processing pipelines for parsing and analyzing unstructured content. Your role will involve designing and optimizing machine learning models, managing MLOps functions, and collaborating with teams to enhance the solutions. The focus will be on integrating these solutions into existing products and improving the retrieval and analysis of engineering data.
The Senior/Lead Data Science Engineer will design and implement ML solutions, collaborate with stakeholders to understand requirements, and develop models for batch and real-time operations. Responsibilities include leveraging Generative AI, analyzing data, and continuously improving models based on new data and business needs.
The MEU S4o9 Data & Analytics Lead bridges the gap between functional and technical teams during the S4o9 transformation project, ensuring that business requirements are translated into effective technical solutions. Responsibilities include driving data and analytics deliverables, conducting impact analysis, ensuring successful migrations in the S/4HANA environment, and collaborating with stakeholders to meet business objectives.
The Data Science Lead will manage data science projects, enhance and monitor the digital twin model's accuracy, and collaborate with cross-functional teams to translate business needs into analytical solutions. The role involves guiding data strategy, developing performance metrics, and mentoring team members to foster innovation.
As a Data Scientist, you will evaluate business problems, source data, train or select models, and collaborate with engineers and developers to deploy solutions. You'll focus on scaling AI capabilities within the organization while enhancing productivity and decision-making through data products.
As a Senior Data Scientist at CreatorIQ, you will lead the development of machine learning projects, optimize algorithms, and work with large datasets to identify modeling opportunities. Collaborating with clients and internal teams, you'll present findings to stakeholders while maintaining data science best practices.
As a Senior Data Scientist in Location Intelligence, you'll drive data-driven insights through geospatial analysis, predictive modeling, and collaboration to optimize delivery routes and enhance decision-making. Key tasks include data management, automation, and communication of insights to stakeholders, with a focus on improving operational excellence.
The Data Science Analyst role involves assessing the value of ML projects, analyzing the ML pipeline, and mining data to validate hypotheses. Responsibilities include designing experiments for ML, developing methodologies, and working with data visualization tools. Technical skills in Python and SQL are essential for this position.
Featured Jobs
The Head of Growth will lead a team focused on driving commercial results using data and technology. Responsibilities include managing the marketing technology stack, overseeing customer lifecycle analytics, optimizing lead conversion rates, developing SEO practices, and collaborating with various departments to implement data solutions.
The Principal Data Science Engineer at Sabre will utilize statistical analysis and machine learning techniques to optimize revenue performance and customer experience in the airline industry. Responsibilities include developing data models, algorithms, and forecasting techniques, collaborating with software engineers, and monitoring data accuracy and model performance. Required qualifications include an advanced degree in quantitative disciplines and proven analytical skills.
The Data Scientist Manager at U.S. Bank will lead a team responsible for monitoring the performance of predictive models used in Credit Risk Management. Key responsibilities include overseeing model monitoring processes, validating outputs, automating data capture, and mentoring team members.
The Data Science Analyst role involves working within the Data Analytics team to assess the incremental value of machine learning projects, analyze the entire ML pipeline, design experiments such as A/B tests, and enhance methodologies in an internal Python library. Candidates should have strong analytical skills, practical knowledge of Python and SQL, and be comfortable working with data visualization tools and statistical concepts.
The Data Modeller will design and implement data models, ensuring they meet standards for reliability and performance. Responsibilities include driving automation in data modeling, establishing principles and standards, leading key data products, and sharing knowledge with the team. The role requires collaboration in a dynamic, multicultural environment.
The Solutions Engineer will lead technical sales processes, design customer solutions using Cloudera technologies, and build relationships to ensure client success. Responsibilities include conducting demonstrations, collaborating with account managers, and advocating for customer needs to product management.
The Senior Product Manager will lead market research, analyze product performance, and communicate insights to stakeholders. They will collaborate with development teams to prioritize new features and ensure effective product positioning across cross-functional teams.
Looking for an experienced Manager to coordinate a team with various data roles (Data Analyst/Product Analyst/Data Scientist) shaping Ads products at Allegro. Responsibilities include cooperation in the implementation of the Technology/Product strategy and creation of analytical road-maps.
The Senior Data Engineer/Analyst will design and maintain scalable data pipelines, optimize ETL processes, and build a data warehouse. This role also involves conducting in-depth data analyses for marketing and product performance, developing dashboards, and presenting insights to stakeholders.
The Data Engineer in Product Analytics is responsible for building and optimizing complex data pipelines using tools like Apache Spark and Airflow. They will collaborate with customers to create meaningful dashboards and assist in deploying these processes in a data analytics environment.
The Data Engineer will design and maintain effective databases and data processing pipelines. Responsibilities include performance tuning, resolving database issues, collaborating with developers, gathering user requirements, and supporting data management. The role also involves researching new database products and ensuring compliance with company performance standards.
The Data Scientist will analyze business problems and develop analytical models to provide insights. Responsibilities include data collection, transformation, model design, implementation, and documentation, as well as comparative research on algorithms. The role offers close cooperation with customers and the chance to influence project technologies.
As a Senior Data Scientist at RevenueCat, you will create data models, dashboards, and reports to help developers make informed decisions. You'll collaborate with product and data teams to enhance data features, build predictive models, and contribute to the data tech stack, ultimately shipping features that drive customer value.
The Senior Data Scientist will develop data modeling algorithms to analyze large datasets, ensuring data accuracy and reliability. Responsibilities include bringing data models to production, leveraging AI for workflows, and acting as a subject matter expert in digital advertising.
Design solutions, research and analyze data, develop data science solutions, create ML metrics, mentor team members, suggest improvements, work on machine learning algorithms
The Senior Data Engineer will design and maintain data pipelines, optimize ETL processes, manage the data warehouse in Google BigQuery, implement data quality checks, and collaborate with product teams to enhance data accessibility.
The Senior Data Scientist will build and deploy machine learning models at scale, collaborating with teams across various domains to optimize bidding, predict user behavior, and enhance operational efficiency in the mobile advertising space. Responsibilities include utilizing cloud services, employing ML techniques, and addressing fraud detection and data analytics needs.
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