Data Scientist

위치: China Mainland

시/도 / 도 / 구/군/시: Shanghai

구/군/시: Shanghai

사업 부문: Store Support Centre (SSC)

직무내용 및 자격요건

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.

Position
Data Scientist

Reports to
Senior Manager, Data Solution

Location
Shanghai

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. 

Core responsibilities
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
Acknowledge the presence of choice in every moment and take personal responsibility for your life.
Possess an entrepreneurial spirit and continuously innovate to achieve great results. 
Communicate with honesty and kindness and create the space for others to do the same. 
Lead with courage, knowing the possibility of greatness is bigger than the fear of failure. 
Foster connection by putting people first and building trusting relationships. 
Integrate fun and joy as a way of being and working, aka doesn’t take yourself too seriously. 

Additional notes
Authorization to work in China is required for this role.


Compensation and benefits package 
lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. As part of our total rewards offering, you will receive competitive base pay and permanent employees in this position may be eligible for our annual bonus program, subject to program eligibility requirements.   

At lululemon, investing in our people is a top priority. We believe that when life works, work works. We strive to be the place where inclusive leaders come to develop and enable all to be well. Recognizing our teams for their performance and dedication, other components of our total rewards offerings include support of career development, wellbeing, and personal growth:
Supplement health and dental benefits, and mental health plans
Paid time off
Savings plan matching - Employee Stock Purchase Plan
Generous employee discount
Fitness & yoga classes
Parenthood top-up
Extensive catalog of development course offerings
People networks, mentorship programs, and leadership series (to name a few)

Note: The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice.

workplace arrangement

In Person
In-person collaboration and office-based work is necessary and important for this role. Work is performed onsite, 5 days a week, depending on role requirements.