Yes4All is one of the leading brands for home sporting goods & furniture in the e-commerce market. Founded in 2010, we have strived to be the world leader in e-commerce enablers in term of trading, product creating and e-commerce servicing. Based in California with an operation office in HCMC, we have more than 500 young and talented members with expert knowledge and experience in the e-commerce industry.
We are on an ambitious journey to dominate not only US e-commerce market but also to enter new e-commerce markets of more than 15 countries in Europe, Asia and North America, not only Amazon channel but also Walmart, Wayfair among others. Besides, Home sporting goods, Furniture, Outdoor and Gardening are also great opportunities that we desire to occupy and create significant values. With our steady knowledge in E-commerce, Yes4All started to provide end-to-end ecommerce-enabler service in order to help Vietnamese and global manufacturers or struggling sellers bring their products to the US & International markets.
Our mission: Connect the Worldwide Resources & create innovative platform to bring products and services from innovators and manufacturers to worldwide customers more efficiently.
Our vision: To be the world leader of e-commerce enabler in term of trading, product creating, and e-commerce servicing.
I. JOB PURPOSE
As an Analytics Engineer, you will play a key role in building and optimizing our data infrastructure to support data-driven decision-making across the organization.
II. RESPONSIBILITY AND AUTHORITY
- Level 1: The person is assigned the right determine issues, make the solution, identify the benefits and risks of each solution and propose an optimal solution to superior for approval
- Level 2: The person is assigned the right to present the direct superior what is intent to do and seek guidance before deciding
- Level 3: The person is assigned the right to directly solve the problems and report on the works & results achieved
- Level 4: The person is assigned all the rights of decision and not have to report working results to direct superior except the request
1. Data Pipeline Development: Build and maintain scalable and efficient data pipelines to ingest, process, and transform large volumes of data from diverse sources. Ensure data quality, reliability, and integrity throughout the pipeline.
2. Data Modeling and Analysis: Build predictive models and machine-learning algorithms to analyze large amounts of information to discover trends and patterns. Develop state-of-the-art model/algorithms in one or all the following areas: deep learning (convolutional neural networks, NLP, computer vision), object detection/classification, model fusion based on different data modalities (e.g., text, images, videos), etc.
3. Tool and Technology: Implement analytics tools and technologies to optimize team’s performance as well as support the
4. Implementation: organization's analytical needs through automation process and technology adoption.
5. Tool and Technology Selection: Evaluate, select, and implement analytics tools and technologies to support the organization's analytical needs. Research & stay abreast of emerging technologies and industry trends in data and analytics.
6. Collaboration and Support: Collaborate with cross-functional teams (such as DE, BI, Sales) to support their data and analytics needs. Provide technical guidance and support to team members if needed.
7. Documentation and Training: Document technical specifications, data models, and processes. Provide training and support to end-users on data tools and platforms.