Build an integrated customer database and correlate data across the customer journey with Yamaha, delivering Machine Learning solutions for customer clusters with similar behaviors.
Generate insights to improve customer lifecycle and engagement strategies.
Define lead strategy and monitor leads, managing internal BI and supporting the dealer network.
Train and support consultants and the dealer network based on data analyses and results.
Review messaging, conversion results and ROI, conducting deep analyses and recommending optimal investment approaches.
Oversee support activities provided by interns.
Produce local reports and reports for corporate headquarters.
Perform practical statistical analysis with a solid understanding and application of descriptive analysis, probability, regression, inference, hypothesis testing, optimization models and quantitative methods, aiming to forecast motorcycle demand, estimate price elasticity and make other market-related predictions for the two-wheeler segment.
Create, train and validate models using Machine Learning techniques and best practices.
Develop analyses and presentations; deliver ad-hoc analyses using BI tools and notebooks (Databricks).
Organize materials to generate valuable insights for Marketing regarding communication, marketing strategies, user behavior, forecasts and data products.
Comply with policies and procedures, meeting the objectives and targets of the Quality Policy (ISO 9001) and the Environmental Management System (ISO 14001).
Participate in the environmental awareness program and the Environmental Management System in general.
Requirements
Bachelor’s degree in Mathematics, Statistics, Physics, Engineering, Computer Science, Marketing or related fields (completed)
Advanced English
Advanced Power BI
Advanced Excel
Advanced Access
Customer Lifetime Value (CLV/LTV) knowledge
Experience with AWS cloud; experience with Databricks; knowledge of data lake concepts
Knowledge of Machine Learning algorithms (classification, regression, clustering, time series, etc.)
Coding skills in Python, PySpark and SQL
Experience with data visualization
Knowledge of data mining techniques
Experience working with agile methodologies (Scrum, Kanban and/or others)
Critical and analytical thinking
Strong data manipulation skills
Excellent verbal and written communication skills
Creativity
and execution-oriented
Analytical mindset, logical reasoning and problem-solving skills, with a strong ability to manipulate and interpret data, formulate hypotheses and test them quantitatively.