Data Scientist

(60%) Modelling and Statistics
? Partner with internal stakeholders including other Analytics & Insights team members to understand key business problems or needs and develop analytical solutions to address them
? Run analytical experiments in a methodical manner; regularly evaluate alternate models via theoretical approaches
? Brainstorm, create, and iterate on statistical and machine learning models to use in solving business problems and communicate results and ideas to key decision makers
? Consult with business partners to implement tests of collaboratively generated hypotheses as well as models created
? Structure and align on test requirements including populations, cells, exposure and duration
? Construct measurement methodology and timing
? Research and develop statistical learning models for data analysis
? Keep up-to-date with latest technology trends
? Implement new statistical or other mathematical methodologies as needed for specific models or analysis
? Optimize joint development efforts through appropriate database use and project design
? Use unstructured and disjointed datasets for the purpose of independently generating actionable business insights as well as creating manageable analytical processes within the Analytics & Insights
department
(35%) Ad-hoc data
? Prepare data sets for analysis and interpretation
? Create decks and visualizations for company leadership
? Ad-hoc data mining and exploratory statistics tasks on very large data-sets related to the business’s strategies. In this capacity, the Data Scientist will also prepare reports and presentations for senior
data scientists and relevant stakeholders that will give insights for departmental as well as businesswide decision making.
(5%) Provide guidance and support / expand use and expertise of statistics
? Coach other Analytics & Insights team members and functional stakeholders less experienced with statistical methodology
? Develop team members’ skills towards higher statistical proficiency
? Ensure statistical tests are not being misused or results are not misinterpreted
4. QUALIFICATIONS & EXPERIENCE:
? Master’s degree (or Bachelor’s degree with equivalent experience) in a quantitative science such as Statistics or Mathematics and an additional 3-5 years using that experience in a business setting
? Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
? Proficient with scripting and/or programming language, e.g. R, Python; advanced knowledge of data processing, database programming and data analytics tools and techniques
? Extensive background in data mining, modelling and statistical analysis; able to understand various data structures and common methods in data transformation
? Strong communication skills around crafting statistical models and communicating modelling results
? Ability to self-start and self-direct work in a fast-paced environment
? Preferably with two years or more of experience in enterprise database environments
? Understanding of consumer industries such as e-commerce, food tech, retail preferred