Machine Learning Engineer

A "Pricing & Revenue Growth Consultant" advise to build a pricing and promotion tool for CPG client which would have pricing strategies, trade promotions, and revenue growth initiatives. This will involve building analytics and machine learing models for price elasticity, promotion effectiveness, and trade promotion optimization. Consultant would require collaborating with CPG business, marketing, data scientist and other teams for a successful delivery of project and tool.

Required Skills:

• Business Domain Skills:
• Trade Promotion Management (TPM) , Trade Promotion Optimization (TPO) , Trade Spend Efficiency
• Promotion Depth, Frequency, Forecasting, Scenario and Effectiveness
• Price Pack Architecture, Pricing Elasticity and Price Sensitivity
• Competitive Price tracking, benchmarking and effectiveness
• Revenue Growth Management, Category and Channel Growth, Market Entry and New Product Pricing
• Financial Modeling, Dynamic pricing implementation
• AI & Machine Learning for Pricing
• Technical Skills:
• Proficiency in programming languages like Python and R for data manipulation and analysis
• Expertise in machine learning algorithms and statistical modeling techniques
• Familiarity with data warehousing and data pipelines
• Experience with data visualization tools like Tableau or Power BI
• Experience in Cloud platforms (e.g., ADF, Data bricks, Azure) and their AI services.
• Consulting Skills:
• Hypothesis-driven problem solving
• Go-to-market pricing and revenue growth execution
• Advisory, Presentation, Data Storytelling
• Project Leadership and Execution

Typical Work Environment:

• Collaborative work with cross-functional teams across sales, marketing, and product development
• Stakeholder Management, Team Handling
• Fast-paced environment with a focus on delivering timely insights to support business decisions
• Excellent problem-solving skills and ability to address complex technical challenges.
• Effective communication skills to collaborate with cross-functional teams and stakeholders.
• Potential to work on multiple projects simultaneously, prioritizing tasks based on business impact

Qualification:

• Degree in Data Science, Computer Science with data science specialization
• Master’s in business administration and Analytics preferred
• Revenue and Pricing Domain knowledge and experience must have.