Data Science & Strategy Director

AVP / JVP - Analytics & Data Science

Strategy & Practice Development

Contribute to the design, execution, and continuous improvement of the AI and Data Science strategy.

Help build and nurture a data-driven culture and a strong analytics practice within the organization.

Big Data Management & Enrichment

Work with large datasets across sales, consumer, manufacturing, and user attributes.

Identify opportunities to enrich both structured and unstructured data to improve analytical outcomes.

Collaborate with Data Engineering teams to build, enhance, and maintain cloud-based Data Lakes / Warehouses (MS Azure Databricks).

Data Preparation & Single View Creation

Prepare datasets, develop new data attributes, and create unified consumer, retailer, and electrician profiles.

Consumer Insights & Campaign Analytics

Lead ad-hoc and ongoing analyses to uncover insights and improve campaign performance.

Develop a GenAI-powered Consumer Insights Factory to automate and scale insights generation.

Support insight generation across consumer, loyalty, app, sales, and transactional data.

AI / ML Applications & Predictive Analytics

Build and maintain predictive AI / ML models across key consumer, CX, and service-related use cases, such as :

Product recommendations

Purchase propensity and AMC / service likelihood

Lead scoring and conversion prediction

Service risk scoring and technician / franchise performance analytics

Churn prediction and detractor likelihood

Market mix modeling

Conduct deep data mining to support upsell, cross-sell, retention, loyalty, and audience segmentation initiatives.

Dashboarding & Reporting

Work with Data Engineering and Visualization teams to deliver MIS reports and dashboards.

Develop and support Power BI dashboards and other ad-hoc visualizations.

Analytics & Data Science – Cross-Functional Domains (SCM, Sales Operations, Manufacturing, Marketing)

Support AI / ML solutions across multiple business functions, including :

Market mix modeling

Optimization of retailer / electrician loyalty programs

Partner risk scoring and churn prediction

Product placement and channel partner segmentation

Demand forecasting and stockout prediction

Digital analytics (web / app behavior), call center / CS performance, NPS, and loyalty analytics

GenAI Use Cases

Utilize LLMs and agent-based AI to build solutions such as :

Internal business chatbots

Consumer-facing chatbots

Service voice agents

Automated data-mining assistants

Manufacturing-focused GenAI applications

Data Engineering Responsibilities

Support and improve all data engineering activities to maintain a robust cloud-based data infrastructure encompassing data lakes and data marts.

Sustain and optimize the migration of the enterprise data warehouse to MS Azure Databricks.

Build an Agentic AI platform on Vertex.

Enhance data architecture for efficient visualization, ML modeling, and GenAI use cases.

Integrate new structured and unstructured data sources into the Databricks ecosystem.