Head of DataCÔNG TY TNHH DỊCH VỤ THƯƠNG MẠI YES4ALL

Mô tả Công việc
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 DECRIPTIONS
1. Data Strategy & Governance
Develop and implement a comprehensive data strategy aligned with the company's business objectives.
Oversee data governance practices, ensuring data accuracy, privacy, security, and compliance with relevant regulations (e.g., GDPR, CCPA).
Define data standards and best practices for data collection, integration, and processing.
2. Data Architecture & Infrastructure
Lead the design, development, and maintenance of scalable data architectures and infrastructure.
Oversee the implementation of data pipelines, data lakes, and ETL processes to ensure efficient data flow across systems.
Collaborate with engineering teams to integrate machine learning models into production environments.
3. Analytics & Machine Learning
Champion the use of machine learning algorithms to drive business insights, personalization, and predictive analytics in e-commerce.
Work closely with business units (e.g., marketing, sales, customer service) to identify key data-driven opportunities and actionable insights.
Lead the development and optimization of ML models to enhance customer experiences, improve forecasting, and optimize operational efficiency.
4. Collaboration & Stakeholder Management
Partner with senior leadership to define and drive the company's data-driven goals.
Collaborate with product, marketing, and IT teams to ensure alignment on data needs and initiatives.
Present data insights, strategies, and progress to stakeholders in an easily digestible format.
Develop and implement a comprehensive data strategy aligned with the company's business objectives.
Oversee data governance practices, ensuring data accuracy, privacy, security, and compliance with relevant regulations (e.g., GDPR, CCPA).
Define data standards and best practices for data collection, integration, and processing.
Lead the design, development, and maintenance of scalable data architectures and infrastructure.
Oversee the implementation of data pipelines, data lakes, and ETL processes to ensure efficient data flow across systems.
Collaborate with engineering teams to integrate machine learning models into production environments.
Champion the use of machine learning algorithms to drive business insights, personalization, and predictive analytics in e-commerce.
Work closely with business units (e.g., marketing, sales, customer service) to identify key data-driven opportunities and actionable insights.
Lead the development and optimization of ML models to enhance customer experiences, improve forecasting, and optimize operational efficiency.
Partner with senior leadership to define and drive the company's data-driven goals.
Collaborate with product, marketing, and IT teams to ensure alignment on data needs and initiatives.
Present data insights, strategies, and progress to stakeholders in an easily digestible format.