S&C Global Network - AI - CG&S Analyst Data Science

Entity :- Accenture Strategy & Consulting

Team :- Applied Intelligence, Accenture Strategy & Consulting

Practice :- CG&S

Title :-

I&F- Decision Science AI/ML Manager

Job location :- Bengaluru

WHATS IN IT FOR YOU?

Accenture will continually invest in your learning and growth. Youll work with Accentures certified Data & AI practitioners, and Accenture will support you in growing your own tech stack and certifications.

Youll be part of a diverse, vibrant, global Accenture Data & AI community, continually pushing the boundaries of business capabilities .

What you would do in this role
We are seeking a skilled and experienced MLE Manager to join our team. The ideal candidate should have a strong background in working in different cloud environments( GCP, Azure or AWS), CI\CD WoW, Migration process, MLOps , LLMOps and Data Engineering.
Responsibilities:
Role:ML Engineer Manager

Responsibilities:

Lead and manage a team of machine learning engineers, overseeing the development and deployment of machine learning solutions for clients within the CG&S domain.

Provide strategic direction, mentorship, and support to team members, nurturing their professional growth and expertise .

Collaborate closely with CG&S clients and stakeholders to comprehend business requirements and user needs, translating them into actionable strategies for the development of machine learning models.

Offer strategic consultation and guidance to internal stakeholders on machine learning principles, tools, and methodologies, including Azure Services, Data Science, Python, and DevOps/GitHub integration.

Lead collaborative sessions and supervise the creation of advanced data pipelines and models, utilizing expertise in data assessment, modeling, data feature synthesis, and conducting data quality checks.

Drive the creation and implementation of analytical models, including LLM and Generative AI techniques, to address complex business challenges.

Stay abreast of emerging trends and best practices in machine learning and cloud technologies, sharing insights and recommendations with the team.

Collaborate with data scientists, analysts, and engineers to seamlessly integrate machine learning models into data-driven applications and products.

Contribute to thought leadership initiatives within the organization, such as blog posts, whitepapers, and presentations, to showcase expertise and foster knowledge sharing.

Manage project timelines, budgets, and resources effectively to ensure the timely delivery of high-quality machine learning solutions.

Contribute to business development efforts by providing expertise and insights for RFP responses, client presentations, and proposals, identifying opportunities for growth and contributing to the development of strategies to expand the machine learning practice.

Qualifications

Who we are looking for:

Minimum of 7 to 10 years of experience in machine learning engineering, data science, or related roles, demonstrating a strong portfolio of successful projects and achievements.

The candidate should be experienced in dealing with CG&S data (Nielsen, EPOS, IRI, Kantar, Euromonitor, Manufacturer or retailer P&L - financials, SAP, Sales & operations, Demographics, Trade promotion planner etc.) & functions (such as Customer Experience, Marketing and Promotions, Store Planning, Supply Chain and Logistics, and trade promotions, salesforce etc.) driven through AI.

Proficiency in Azure Services, Python programming, and DevOps/GitHub for developing and deploying machine learning solutions.

Extensive experience in data assessment, modeling, data feature synthesis, and conducting data quality checks to ensure accuracy and reliability.

Proven track record in analytical model creation, utilizing techniques such as LLM (Large Language Models) and Generative AI to derive actionable insights.

Substantial knowledge and expertise in project management, with the ability to effectively lead and manage complex ML projects from conception to delivery.

Deep understanding of cloud agnostic environments, including AWS, Azure, and GCP, with a focus on building robust data pipelines for diverse datasets such as Nielsen, Kantar, IRI, EPOS, public data, E-Comm, and Brand Health data.

Prior consulting experience preferred, demonstrating the ability to lead and manage consulting engagements, drive client interactions, and deliver value-added solutions.

Excellent communication and collaboration skills, with the ability to convey complex concepts and insights to diverse stakeholders effectively.

Experience working in agile environments and collaborating closely with cross-functional teams to deliver impactful solutions.

A background in statistics, mathematics, or related quantitative fields is preferred, with additional qualifications such as an MBA from a premier business school considered a plus.