A Day in the Life of a Data Scientist
[Hamza Farooq]
9/8/17
Capabilities Overview
Liaison with UI
and Backend to
deliver end-toend Integration
Create Data Pipeline
and Algorithm
implementation
within Hadoop
Clusters
Create data using various
tables to provide
richness
Deployment
Data
Augmentation
Scalability
Algorithm
Design
Create Algorithms
pertaining to the
veracity of Wal-Mart
Data
Use Case
Use Case 1:
Wrigley’s estimates $65 million in
lost gum sales annually at
Walmart due to on shelf stock outs
Other highly impacted impulse
items include Mint, Candy, Yogurt,
Frozen, Cookies and Chips
However, every other category is
also impacted to a considerable
Degree
This significantly impacts bottom
line of both Walmart and Supplier
Use Case 2: Iterative Customer Decision Tree
Relationships between products determine the structure of customer decision tree (iCDT).
The iCDT works to identify the customer thought process and also highlights online product segments not carried in stores.
Example 1
Headphones
Example 2
Food Storage
SINGLE/DOUBLE
Not carried in stores
MULTI
Use Case 3: Objective is to solve for the amount of demand that is
transferred when an item is removed from an assortment
Example: CDT Node (all the items in a node are substitutes)
If Removed…
A
B
C
D
E
How will demand change for remaining items B-E?
How much demand will not transfer?
API based Hadoop Architecture
Enterprise Assortment System [UI]
API
The new architecture allows
scalability using Hadoop Clusters and
deliver results faster and seamless
integration within the
UI.
All jobs are executed within the edge
nodes using the Oozie workflow
which allows 100% automation and
brings the need for manual
intervention to zero
Seamless Integration
between each layer
Seamless
Integration
between
each layer