Revenue Growth Manager (RGM) - Senior Consultant (CPG)

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Brief About Fractal :

Fractal is one of the most prominent providers of Artificial Intelligence to Fortune 500® companies. Fractal's vision is to power every human decision in the enterprise, and bring AI, engineering, and design to help the world's most admired companies.

Fractal currently has 4000+ employees across 16 global locations, including the United States, UK, Ukraine, India, Singapore, and Australia. Fractal has been recognized as 'Great Workplace' and 'India's Best Workplaces for Women' in the top 100 (large) category by The Great Place to Work® Institute; featured as a leader in Customer Analytics Service Providers Wave™ 2021, Computer Vision Consultancies Wave™ 2020 & Specialized Insights Service Providers Wave™ 2020 by Forrester Research Inc., a leader in Analytics & AI Services Specialists Peak Matrix 2022 by Everest Group and recognized as an 'Honorable Vendor' in 2022 Magic Quadrant™ for data & analytics by Gartner Inc. For more information, visit https://fractal.ai/

Job Summary:

We are looking for an experienced Senior Consultant who will lead client projects in RGM for CPG. 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. 

Context & Scope
This role sits within our CPG practice, and reports into the RGM Client delivery lead at Fractal. We continue to deliver services in RGM to our clients, and this platform is to accelerate the setup & scale of that journey. 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 in CPG domain. 

• ·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

• ·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, RGM/CPG 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.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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