- Data Analyst
- Bangalore , IN
2023-11-06 09:45:32 UTC
Pollen Tech Pte Ltd is a private B2B marketplace that helps companies buy and sell excess inventory sustainably, with a focus on reducing business waste. As a Data Engineer, you will work as part of a dynamic team to support the development and implementation of data-driven solutions for Pollen's platform. You will be responsible for creating data models used by Pollen customers. The ideal candidate will have a strong technical background and be passionate about using data to drive business decisions and improve customer experience.
- At least 3 years of working experience in data science, with a bachelor's degree or above, majoring in quantitative field statistics is preferred. - Proficient in SQL, Python or R, and expertise in at least one of the three areas: advanced measurement (e.g causal inference or systems with complex trade-offs), modeling, and optimization. - E-commerce or online marketplace experience is strongly preferred. - To succeed in the role, you need to be a proactive, self-driven and impact-driven person. - Be able to work with cross-functional teams in a fast-paced environment.
Bachelor's degree in Computer Science, Information Technology, or a related field.
Minimum of 3 years of experience in data engineering or a related field.
Strong programming skills in languages such as Python, Java or Scala.
Hands-on experience with cloud-based data platforms such as AWS
Experience with data warehousing, ETL, and data modeling techniques.
Excellent problem-solving skills and attention to detail.
Working experience in one of the following fields: machine learning, NLP, and computer vision • Experience with software development in at least one of the following programming languages: C++, Python, Go, Java, SQL, can use Python or R for data analysis
• Good sense of teamwork and communication skills, practical experience in relevant business scenarios is preferred.
- Proficient in using at least one mainstream deep learning framework such as Tensor Flow/PyTorch, understanding distributed training, distillation acceleration, and other implementation methods.
- Experience in text classification, text matching, sequence labeling, knowledge graph.
- Aware of certain processing methods and optimization experience on domain adaptation, small sample construction, text mining, unsupervised/semi-supervised, and other similar issues.
- Familiar with commonly used machine learning and deep learning algorithms, understand basic network model structure (DNN/LSTM/CNN, etc.) and text representation methods (LDA/Word2 Vec/ELMo/GPT/BERT, etc.), have practical experience in deep learning training and reasoning model tuning.
- Experience in large-scale text data processing or cleaning (Such as using Hadoop/Spark/Hive/Flink).