地点: China Mainland
州/省/市: Shanghai
城市: Shanghai
业务单元: Store Support Centre (SSC)
Data Scientist
说明与要求
Who we are
lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people.
About this role
We are seeking a highly technical and experienced Data Scientist with a strong foundation in data science to lead the ideation, development, and launch of our next-generation AI/ML-powered products and features. The overarching key role of this position is to extract meaningful value and actionable insights from data to drive strategic decision-making, solve complex problems, and create competitive advantages. In this unique role, you will act as the crucial bridge between complex business needs and advanced technical capabilities. You will leverage your deep understanding of data science principles, machine learning algorithms, and data infrastructure to define data science strategy, guide development teams, and ensure AI solutions deliver significant user and business value. You are not just defining what to build, but also deeply understanding how it can be built effectively and responsibly.
A day in the life:
- Identifying & Frame Opportunities: Proactively finding areas where data analysis and modeling can improve processes, products, or strategies, exploring new data sources, techniques, and technologies to uncover novel insights and create new opportunities, engage with business stakeholders/cross teams to deeply understand their challenges & needs.
- Develop and Implement Data Acquisition: Identify necessary internal and external data sources. Collaborate with Data Engineers to ensure data pipelines are built or available to collect, integrate, and access the required data reliably.
- Perform Rigorous Data Preparation and Feature Engineering: Clean, transform, and structure large, often complex and messy, enterprise datasets. Create meaningful features (variables) that accurately represent the underlying business process and improve model performance.
- Conduct Exploratory Data Analysis for Actionable Insights: Analyze data to uncover significant trends, patterns, correlations, and anomalies. Generate hypotheses and initial insights that can inform business strategy even before formal modeling.
- Build, Train, and Tune Predictive/Prescriptive Models: Select appropriate statistical or machine learning algorithms (e.g., for forecasting, classification, clustering, optimization). Develop, train, and iteratively refine models using sound methodologies to address the defined business problem.
- Validate Model Performance and Ensure Robustness: Design and execute rigorous testing and validation strategies (e.g., cross-validation, hold-out sets, A/B testing framework design) to assess model accuracy, reliability, fairness, and generalizability before deployment. Understand and articulate model limitations.
- Communicate Findings and Recommendation: Present complex analytical results, insights, and model behaviors clearly and concisely to diverse audiences, including non-technical stakeholders. Use data visualization and storytelling to drive understanding and decision-making.
- Model Deployment and Operationalization: Work closely with Machine Learning Engineers, Data Engineers, and cross functional teams to integrate models into applications Provide necessary documentation and specifications.
- Monitor Model Performance and Maintain Lifecycle: Track the performance of deployed models over time to detect drift or degradation. Define strategies for retraining, updating, or retiring models as needed to ensure continued value and accuracy.
- Quantify Business Impact and Advocate for Data-Driven Culture: Measure and report on the tangible value delivered by data science initiatives. Champion the use of data and evidence-based decision-making across the organization.
Qualifications:
- Master's or PhD in Computer Science, Data Science, Statistics, or a related quantitative field, 3-5+ years of professional experience in AI projects, adept at applying agile and design thinking. methods
- Previous hands-on experience working as a Data Scientist, ML Engineer, or equivalent technical role, Experience building or managing products specifically leveraging AI/ML (e.g., recommendation systems, GenAI, Predictive analytics).
- Solid experience in working with Large Language Models, Retrieval-Augmented Generation, and other AI technologies, especially in applying these technologies to solve complex problems and improve business processes. Familiarity or hands-on experience with Generative AI concepts and techniques (LLMs, prompt engineering, fine-tuning, RAG).
- Understanding of data infrastructure, ETL processes, and cloud platforms commonly used for ML workloads, Knowledge of MLOps principles and practices (model deployment, monitoring, retraining).
- Experience in leading and developing communication and engagement strategies to drive clarity and understanding of transformation initiatives within the organization, Excellent analytical and problem-solving skills with a critical thinking mindset.
- Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and AI engineering.
- Fluent in Chinese and English, able to present complex technical and business concepts clearly and convincingly to various stakeholders.
Must haves:
- Thrives in a rapidly evolving environment and comfortable with ambiguity
- Demonstrate the ability to multi-task and work under pressure
- Acknowledges the presence of choice in every moment and takes personal responsibility for their life
- Possesses an entrepreneurial spirit and continuously innovates to achieve great results
- Communicates with honesty and kindness, and creates the space for others to do the same
- Leads with courage, knowing the possibility of greatness is bigger than the fear of failure
- Fosters connection by putting people first and building trusting relationships
- Integrates fun and joy as a way of being and working, aka doesn’t take themselves too seriously
只有被纳入考量范围的申请人才会收到我们的联络。非常感谢您有意申请我们的职位。lululemon 是支持公平就业机会的雇主。雇佣决策基于价值和商业需求，与种族、肤色、信仰、年龄、生理性别、社会性别、性取向、国籍、宗教、婚姻状况、健康状况、身体或精神残疾、兵役、怀孕、分娩和相关医疗情况，或受联邦、州或省及地方法律和法令保护的任何其他因素无关。符合资格的残障人士可根据要求获得合理便利。“公平就业机会”政策适用于与招募、雇佣、报酬、福利、惩戒、转岗、终止雇佣相关的所有操作以及其他所有雇佣条款与条件。虽然管理层主要负责“公平就业机会”政策的实施，但员工也应通过个人行动负责确保政策的有效性。
lululemon is committed to providing reasonable accommodation to applicants with disabilities. If you would like someone from our team to contact you for individualized support, email us ataccommodations@lululemon.com. In your email, please include the position title, the location of the position and the nature of your request.