Job Responsibilities
Participate in the full lifecycle design and development of data products, including product research, solution design, data pipeline construction, data mining and modeling, as well as continuous product maintenance.
Be responsible for data collection, cleaning, storage, and analysis to support business decision-making optimization and drive data-driven business model transformation and growth.
Deeply understand of business requirements and data requirements, design and implement efficient data processing workflows, and enhance the stability and performance of data systems.
Collaborate with business teams to explore the application potential of data in multiple scenarios, supporting product innovation and business growth.
Write high-quality technical documentation to support technology transfer and knowledge sharing of data solutions.
Job Requirements
Familiarity with big data tools and frameworks (such as Hadoop, Hive, Spark, Kafka, Sqoop, etc.). Relevant development experience is preferred.
Proficiency in data analysis and machine learning libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, with the ability to independently complete end-to-end tasks from data cleaning, feature engineering, model training, evaluation, to debugging and deployment.
Proficient in SQL, capable of writing complex SQL queries (multi-table joins, window functions, subqueries, CTEs), and familiar with big data query tools like Hive and Spark SQL.
Skilled in using relational and non-relational databases such as MySQL, PostgreSQL, and Redis, with knowledge of database mechanisms and performance optimization techniques. Proficient in SQL or other data analysis tools.
Ability to implement complex statistical formulas, attribution analysis, and causal inference models using Python and SQL.
Solid data processing and analysis skills, capable of designing and implementing efficient data processing workflows. Deep understanding of data-driven business models, with the ability to translate data into business value.
Strong teamwork spirit, able to efficiently participate in cross-departmental collaborative projects and drive the implementation of data solutions.
Bachelor’s/Master’s degree in Computer Science, AI, or a related field.
2-5 years of experience in data processing and data engineering.
Engineering experience with Agent or Prompt Engineering is preferred.
Strong proficiency in English across listening, speaking, reading, and writing.
