7 results
FiltersCreate natural, realistic Q&A pairs that mirror how users interact with SQL query results, ensuring linguistic clarity and logical alignment, focusing on SQL queries and corresponding result tables to craft questions reflecting real user scenarios and information needs. Verify consistency between question intent, query logic, and data output.
In this role, you will develop and optimise core algorithmic models in marketing scenarios. Responsibilities include user behaviour prediction, profiling, ROI estimation, and traffic allocation strategies. You will design and build precision marketing models such as CTR/CVR prediction, LTV forecasting, and channel attribution analysis.
Seeking an experienced and dynamic Azure Data Engineer to lead data engineering engagements, design scalable data solutions, and help clients unlock the full potential of their data. The candidate will act as a trusted advisor, providing technical leadership and strategic guidance while working on cutting-edge Microsoft Azure technologies.
Contribute directly to the future of AI in your language with CrowdGen. Flexible participation is offered, allowing you to work anytime, anywhere. Complete a one-time task in just a few hours by recording 500 short, scripted commands in Cantonese and English. To qualify for payment, at least 90% (450 recordings) must pass quality review. If selected, you will receive an email from CrowdGen regarding the creation of an account. Ready to make your voice count in AI?
Research and analyze risk patterns occurred on Binance platforms, using data driven thinking and quantitative analysis methodologies to identify, measure, contain and mitigate risks (e.g. fraud trading, spam registration, account takeover, card acquiring risk and payment fraud). Deploy, monitor and assess the effectiveness and stability of variables, rules and models, maintain and iterate the rules/strategies regularly to improve key risk matrix.
Design, implement, and maintain scalable data pipelines using Snowflake, Coalesce.io, Airbyte, and SQL Server/SSIS, with some use of Azure Data Factory. Build and maintain dimensional data models to ensure high-quality, structured data for analytics and reporting. Implement Medallion architecture in Snowflake, managing bronze, silver, and gold layers. Collaborate with teams using Jira for task tracking and GitHub for code repository management.
Design, build, and manage data warehouse to serve as the single source of truth for the organization. Develop and deploy low-latency, real-time data streaming pipelines. Enable self-service analytics by building clean, well-documented, and trusted datasets. Establish and follow data governance and security best practices. Stay current with industry best practices and emerging data analysis tools and techniques.