RGM Consultant at Fractal

Job Summary:
We are looking for an experienced Senior Consultant who will lead client projects in RGM for Consumer durables. In this role, you will be responsible for maintaining, tuning, and upgrading the existing models, working closely with cross-functional teams to ensure successful data, modeling deployment. The ideal candidate will have deep 
understanding of the data science in CPG industry and RGM in particular.

This role must engage, influence and inspire wide variety of stakeholders internally from AI, Engineering & Design in order 
to drive collaboration and alignment.

Knowledge/Skills

• 5+ years of work experience related to RGM data science, analytics.
• Creative thinker, Strategic thinking, Analytical and problem-solving skills
• Attention to details, Discipline, Active listening, Outstanding communication, presentation and leadership 
skills
• Organizational and time management skills. Management of stakeholders and their expectations
• Ability to design solution frameworks with minimal guidance and lead client discussions
• Strong knowledge of machine learning and statistical modeling techniques, with some exposure to cloud 
technologies such as Azure Databricks
• Experience with programming languages such as Python, Spark; or working closely teams who work with 
these programming languages
• Strong understanding of CPG data sources, algorithms, and software design principles, highly sensitive to 
algorithm complexity

Key Responsibilities
• Enable build, Maintain, refine/tune and upgrade the data science engine. Configure multiple AI pipelines and run the 
engine
• Use data wrangling and exploration to extract insights and relationships from the data
• Perform descriptive analysis and build visualizations to help customer understand what drives the 
business metrics.
• Conduct research and prototyping innovations; data and requirements gathering; solution scoping and 
architecture; consulting clients and client facing teams on advanced statistical and machine learning 
problems.
• Collaborate and coordinate with different functional teams (engineering and product development) to 
implement models and monitor outcomes. Work with engineering and design teams, leadership to develop product requirements and user stories
• Lead technical and business discussions with the customers (mix of KPIs, metrics, data science, data 
engineering, domain discussions Customer management and PoV project management.
• Hold user and stakeholder workshops to show-case results, give overview of model functionality
• Lead a small group of DS developers in collaborate/streamline data science work with product, BA, MLOps
• Leading the collaboration with MLOps to understand the need for industrialization, ensure smooth 
transition from DS development to industrialization by providing sufficient DS support.
• Code development/redevelopment planning, provide direct support to DS developers in the execution.
• Ensure proper code standard are enforced, complete documentation is created and strong code 
management through version control. Leading regular code review together with the data scientist 
project lead.
• Ensure a common code base is created for efficient roll-out in new market with highly modular 
architecture, well designed data abstraction, high configurability and high level of parameterization