Senior Data Scientist
Sr. Data Scientist
Who We Are
lululemon is a yoga-inspired technical apparel company up to big things. The practice and philosophy of yoga informs our overall purpose to elevate the world through the power of practice. We are proud to be a growing global company with locations across North America, Australia and New Zealand, Europe, and Asia. We owe our success to our innovative product, our emphasis on our stores, our commitment to our people, and the incredible connections we get to make in every community we are in.
About This Role
The Sr. Data Scientist is an exceptional critical thinker comfortable leading end-to-end data science projects, and passionate about uncovering hidden opportunities deep within data. The Sr. Data Scientist works with business partners to define the business problem and creates a solution approach with small core project teams. This individual then takes the approach all the way to implementing data products, in collaboration with technology teams and other members of the Data Science team. The Sr. Data Scientist will lead data science work streams for the most difficult problems facing our Product functions in areas such as merchandising, merchandise planning, and allocations.
A day in the life
Lead data science projects from start to finish, identifying opportunities, defining the problem, building a proof of concept, and deploying a data product
Conduct data mining on guest, product, sales, assortment data sources for insights; generate hypotheses to test for opportunities in improving the merchandising and planning process
Apply a wide range of statistical and quantitative analysis in practical and valuable ways
Perform data pre-processing, data engineering, feature selection, model selection analysis
Participate in design workshops and document business requirements and constraints
Work closely with product managers to define requirements and design features
Program and write maintainable and well-documented scripts/applications for process automation; produce reusable machine learning pipelines while model building
Create technical documentation for developed models and processes
Connect with business partners to understand the go-to-market process, product lifecycle, and product strategy
Collaborate with data engineering and ML Ops teams to improve data quality , availability and ensure scripts meet production requirements
Transform data into meaningful conclusions and recommendations
Develop innovative approaches to improve the accuracy of predictions and insights
Research and develop algorithms/Model to improve large scale demand forecasting problem. Build, maintain, and improve new and existing suite of algorithms and their underlying systems.
Use traditional analytics and predictive/statistical modelling techniques to identify and quantify sales drivers, conduct what-if scenario analysis and measure the causal impact of results
Work with the Merchandising, Panning, and Product Management teams to ensure model predictions are consistent with business intuition, explainable and efficiently integrated into processes
Analyzing the AI/ML algorithms that could be used to solve a given problem and ranking them by their success probability.
Collaborate with cross-functional teams to ensure successful implementation of projects
Conduct peer reviews to ensure code standards are met
Visualize and communicate results to senior leadership in Product in a clear and concise manner
Mentor and coach junior data Scientists to help us grow, as a team
Explore and master new technologies to use in your own solutions
Actively contribute towards establishing data science team as thought leader in demand forecasting within the CPG industry.
Monitor industry trends and emerging technologies to identify opportunities for improvement
Stay up-to-date with the latest advancements in data science and applied sciences
Learn and work with subject matter experts
5+ years of work experience in data science, preferably in the retail or apparel industries
Excellent academics in Comp. Science, Engineering, Math, Statistics, Research, or a related field
Strong problem solving and analytical skills including mining, evaluation, analysis, and visualization;
Hands-on experience with production-level data science projects — from prototyping to deploying and maintaining and improving production-ready solutions (i.e. ability and interest to handle a use case end to end).
Deep understanding and experience with forecasting and machine learning, and a solid understanding of statistics.
Experience developing forecasting solutions with practical applications and clear business impact before. For you forecasting is not something you’ve done before amongst other things, it is a domain where you are, and want to be, an expert.
Must have experience with Python (Jupyter, NumPy, Pandas, PySpark)
Must have experience in at least one of the common data science toolkits, such as scikit learn, Tensorflow, PyTorch, etc..
Strong SQL or Excel skills with the ability to learn other analytic tools;
Ability to take on responsibilities and work with minimal to no supervision;
Ability to create and maintain outstanding partner relationships;
Strong technical aptitude;
Excellent written and verbal communication skills including reports and presentations;
A drive to learn and master new technologies and techniques
Demonstrated experience applying machine learning and data mining techniques
Experience of working closely with MLOps to push models to production is preferred
Excellent communication skills to both technical and non-technical audiences
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.