Professional Experience & Qualifications
Required: Undergraduate degree required in a quantitative or technical field such as economics, finance, accounting, engineering, information systems or computer science.
Required: 4-8 years’ experience and demonstrated ability in consultative, analytical, or commercial sales roles.
Required: Familiarity with coding languages including SQL, Python, R, etc.
Required: Familiarity with data processing and visualization tools such as Alteryx, PowerBI, Jupyter Notebooks and the Microsoft Office Suite.
Required: Familiarity with data infrastructure including data warehouses and data lake processing, ex. Snowflake and Databricks.
Required: Demonstrated history of analysis and translation of analytics into practical business outcomes.
Required: History of project work that involved multiple organizational departments and geographic areas.
Required: Significant analytical skills including a passion for data and discovering answers through data manipulation and a highly developed curiosity and motivation for teasing out exciting results.
Required: History of working with and is undaunted by large data sets (those well exceeding a million of records).
Required: A strong baseline of oral and written communication as well as interpersonal skills; an ability to convey complexity in a relatable manner.
Required: Extremely positive, and highly organized; an excellent influencer that exhibits independence and needs little supervision. A Quick learner that exhibits resiliency and tenacity in the face of challenge.
Required: Moves with considerable pace, inspired to act and possesses an insatiable appetite for continuous improvement.
Preferred: Understanding of the US Spirits industry, three-tier system and the data and change management challenges that lie within.
Preferred: Master’s degree in a related field.
Leadership Accountabilities
Indirect management of offshore data science team.
Technical and analytic guidance to onshore peers.
Key Outputs & Results
Development of analytical infrastructure that facilitates the team’s pivot to resources like Databricks and the maximization of those resources.
Further optimization of existing tools so that outputs can come quicker, be more dynamic, and more error-free.
Ad hoc project work and deliverables for commercial and marketing stakeholders.
Support for the core outputs of the EDGE program including Standards, Goals, Trax operations, etc.
Barriers to Success in Role
Inability to scale solutions across existing data platforms.
Inability to grasp nuances and data incongruencies of the US Spirits industry.
Inability build relationships and translate for peers and stakeholders.
Inability to manage through and across a matrixed organization including linking with the wider commercial community.
Aversion to “breaking glass in case of emergency” when quick patch solves are necessary to meet deadlines.
Lack of entrepreneurial drive or an ability to be a self-starter.