Job Description

Management Level:

- Ind & Func AI Decision Science Consultant - Level 9

Location:

Gurgaon / Bangalore / Mumbai / Hyderabad

Functional:

Commercial Analytics (Route to market), Revenue growth management - pricing , promotion, assortment, Descriptive, Diagnostic, Predictive, prescriptive analytics

Analytics Models knowledge:

Econometric Modeling, Statistical Timeseries Models, Store Clustering Algorithms, Causal models, State Space Modeling, Mixed Effect Regression, NLP Techniques, Large Language Models, non-parametric models, AI/ML model development, Supervised and unsupervised learning models, Agentic frameworks, Generative AI models.

Technical:

Azure ML Tech Stack, SQL, PySpark, Python, Cloud Platform Experience (Azure, GCP), Data architecture, Data modeling & Pipelines, Power Platform (BI + App), Tableau, Custom Frontend

Soft skill:

Client Management, Verbal and written communication, Team collaboration skills, e-mail writing, PowerPoint and Excel reporting, pro-active initialization, accountability

Industry Knowledge:

CPG, FMCG, Retail

Good to have skills:

AWS knowledge Cloud Capability, Scalable Machine Learning Architecture Design Patterns, AI Capability Building, React, Angular Front end build, Dev Ops pipeline creation.

Experience:

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


3+ years of experience in commercial analytics domain.

Educational Qualification:

Bachelor/Master's 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.

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/Master's 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.

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