Project: Timeseries revenue and inventory forecasting, market basket analysis, ETL
Tools: Databricks, AWS Glue, Python, Pyspark, SQL
Key Responsibilities:
Identify and present predictive drivers/leading indicators, trends, outliers, and patterns that uncover new insights to help guide enterprise-wide business insights
Perform AB & multi-variate testing to measure impact of identified initiatives
Build optimization models for scenario testing future business outcomes based on internal and external data
Be able to ‘tell a story’ using advanced analytics and data visualization techniques while independently exploring useful insights that identify incremental revenue and efficiency opportunities within the financial COE team
Derive data driven insights in close partnership with Finance, Operations, Commercial, and Data Science teams to expose opportunities for revenue and cost optimization with resource allocation
Requirements
Requirements/Qualifications:
Bachelor’s degree in Mathematics, Computer Science, Data Science, Applied Statistics, or a related field, Master’s preferred
3+ years’ experience building statistical modelling tools & underlying algorithms, optimization / machine learning, and data mining models
Experience analyzing large, complex data sets yielding opportunities for revenue and/or process improvement within an organization
Ability to problem solve and identify creative solutions.
Programming experience (SQL, R, Python) required. Databricks experiences a plus.
Understanding of data lakes and relational databases
Experience in data visualization tools (Power BI, Tableau, SAS Analytics) a plus
Interpersonal skills: exceptional verbal/written communication, listening and presentation skills with attention to detail
Proven track record of achieving desired results without direct report authority
Knowledge of Agile/Scrum methodology a plus
Required profile
Experience
Level of experience:Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.