Data Scientist, Vanilla Steel

• At least 2 years of experience working in data science or machine learning or statistical modeling
• Experience working with data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. Matlab)
• Experience working with Product and Business stakeholders in order to understand the customer problems and goals for which you would be building out data centric solutions
• Ability to communicate and work well with Technology teams to take the solution to the actual end user
• An exceptional understanding of data analysis tools, techniques and limitations, statistics concepts, and A/B testing
• Experience applying theoretical models in an applied environment
• A degree in Computer Science, Mathematics, Statistics or another quantitative discipline
• Excellent communication skills (both verbal and written) and confidence in presenting ideas and findings to stakeholders with the right level of detail
• Experience with using solutioning approaches like Opportunity Solution Tree or something similar in order to independently identify top opportunities is nice to have

Desirable

• As a Data Scientist, your primary contribution will be to develop our material matchmaking algorithm from zero to one, enabling spotting of new transactions and realizing direct impact on new transaction growth
• Work closely with Product to understand customer/business needs, success metrics and priorities to plan out your own solution space and roadmap
• Develop material recommendation algorithms based on live material inventory, purchase behavior and buying preferences
• Develop models and algorithms to aggregate, clean, structure and standardize supplier inventory data from various data sources and formats including Excel, PDF, ERP and unstructured natural language
• Design and analyze large-scale A/B tests to continuously improve and iterate algorithm performance
• Evaluate algorithm performance to identify improvement opportunities
• Proactively communicate, share your conclusions, and explain complex topics tailored to diverse audiences
• Push new ideas into the design and concept funnel while keeping business priorities, trade-offs, and technical feasibility in mind
• Create, develop, and maintain metrics on dashboards to measure algorithm performance and the value generated for our customers and for the company