S&C Global Network - AI - Marketing Growth Analytics (DS) - Consultant

Must-have skills: Marketing Analytics, Data Driven Merchandizing (Pricing/Promotions/Assortment Optimization), Statistical Timeseries Models, Store Clustering Algorithms, Descriptive Analytics, State Space Modeling, Mixed Effect Regression, NLP Techniques, Large Language Models, Azure ML Tech Stack, SQL, R, Python, AI/ML Model Development, Cloud Platform Experience (Azure/AWS/GCP), Data Pipelines, Client Management, Insights Communication

Good to have skills:Non-linear Optimization, Resource Optimization, Cloud Capability Migration, Scalable Machine Learning Architecture Design Patterns, Econometric Modeling, AI Capability Building, Industry Knowledge:CPG, Retail

Job

Summary

As part of our Data & AI practice, you will join a worldwide network of smart and driven colleagues experienced in leading statistical tools, methods, and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance.


Roles & Responsibilities:

Working through the phases of project

Define data requirements for Data Driven Growth Analytics capability.

Clean, aggregate, analyze, interpret data, and carry out data quality analysis.

Knowledge of market sizing, lift ratios estimation.

Experience in working with non-linear optimization techniques.

Proficiency in Statistical Timeseries models, store clustering algorithms, descriptive analytics to support merch AI capability.

Hands on experience in state space modeling and mixed effect regression.

Development of AI/ML models in Azure ML tech stack.

Develop and Manage data pipelines.

Aware of common design patterns for scalable machine learning architectures, as well as tools for deploying and maintaining machine learning models in production. Knowledge of cloud platforms and usage for pipelining and deploying and scaling elasticity models.

Working knowledge of resource optimization

Working knowledge of NLP techniques, Large language models.

Manage client relationships and expectations and communicate insights and recommendations effectively.

Capability building and thought leadership.

Logical Thinking Able to think analytically, use a systematic and logical approach to analyze data, problems, and situations. Notices discrepancies and inconsistencies in information and materials.

Task Management Advanced level of task management knowledge and experience. Should be able to plan own tasks, discuss and work on priorities, track, and report progress.

Client Relationship Development

Manage client expectations and develop trusted relationships

Maintain strong communication with key stakeholders

Act as a strategic advisor to clients on their data-driven marketing decisions

Professional & Technical

Skills:

Must have at least 4+ years of work experience in Marketing analytics with a reputed organization.3+ years of experience in Data Driven Merchandizing which involves work experience in Pricing/Promotions/Assortment Optimization capabilities across retail clients.Strong understanding of econometric/statistical modeling:regression analysis, hypothesis testing, multivariate analysis, time series, optimization

Expertise in Azure ML, SQL, R, Python, PySpark

Proficiency in non-linear optimization and resource optimization

Familiarity with design patterns for deploying and maintaining ML models in production

Strong command over marketing data and business processes in Retail and CPG

Hands-on with tools like Excel, Word, PowerPoint for communication and documentation

Additional Information:

Bachelor/Masters degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record

Knowledge of CPG, Retail industry.

Proficient in Excel, MS word, PowerPoint, etc.

Strong client communication.

Qualification

Experience:Must have at least 4+ years of work experience in Marketing analytics with a reputed organization.

3+ years of experience in Data Driven Merchandizing which involves work experience in Pricing/Promotions/Assortment Optimization capabilities across retail clients.


Educational Qualification:Bachelor/Masters degree in Statistics/Economics/Mathematics/Computer Science or related disciplines. Preferred advanced degrees include M.Tech, M.Phil/Ph.D in Statistics/Econometrics or related field from reputed institutions.