Data Scientist Expert with databricks experiance

Build A Customer 360 View: Centralizing customer data view
Multi-Channel Data Collection.
Data ingestion ERP, POS, Loyalty Program, Web Analytics, CRM, Channel Response data, Online behavior and purchase data, Customer Feedback/survey data
Normalize data upstream from other sources
Integrate customer data from multiple sources via API, WebHook
A/B testing capacities to check campaign effectiveness (A vs B)
Real time Customer Segmentation
Behavioral Segmentation ( Clustering)
Micro Segmentation based on rules/lists
Propensity Models
Lookalike Profiling
Cross Sell/ Up Sell Models
CLTV Modeling
Churn Model
Channel Propensity
Arabic Support
Integrated with Punch


KPIs
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What Customers Do
1- Who are our Customers ( Customer Attribution )-DB & Number of Customers

2- Spending per top Customer

3- Geography of Top Customers

4- Top customer by Concept ( What are the items they purchased)

5- Customer Churn Prediction

6- Customer Journey

7- Duration The customer stay in the property

What Customers Say& Why

7- Customer Satisfaction

8- NPS