Specialist - AI Engineering

External Data Science ML Specialist

1 Role Objective

Provide handson Data Science and Machine Learning expertise to develop a Retailer Order Recommendation Engine working under the direction of the internal Project Manager and Lead Data Scientist

Primary scope

Feature Engineering ML Model Recommendation Engine

2 Key Responsibilities

Feature Engineering

Analyse historical retailer ordering data and identify relevant purchasing patterns

Develop features covering order behaviour SKUproduct affinity seasonality retailer attributes and profitability

Build reusable MLready feature pipelines in Databricks

Address data quality missing values outliers and data leakageML Model Development

Develop and evaluate models for SKU recommendationranking and order quantity prediction

Establish appropriate baseline models and performance metrics

Perform model tuning feature selection and historical backtesting

Assess model robustness across different retailer segments

Apply appropriate model explainability techniques Recommendation Engine

Convert ML outputs into actionable retailerspecific recommendations

Develop SKUSKUbundle ranking and quantity recommendation logic

Incorporate profitability and agreed business rules

Generate confidence scores and recommendation driversexplanations

Prepare the engine for integration with the servingAPI layer

Internal

Validation Documentation

Support business validation and refinement of recommendations

Document features models recommendation logic assumptions and limitations

Conduct knowledge transfer to the internal Data Science team

3 Key Deliverables

Feature Engineering Pipeline MLready features and documentation

Validated ML Models SKU rankingrecommendation and quantity prediction models

Recommendation Engine SKUbundle quantity confidence and explanation outputs

Validation Results Baseline comparison model performance and historical backtesting

Technical Documentation Knowledge Transfer

4 Required Technical Skills

Strong practical experience in Data Science Machine Learning

Strong Python and SQL skills

Experience with recommendation systems ranking models or propensity modelling

Experience with transactionalcustomerproduct data

Strong feature engineering and model evaluation skills

Experience with Databricks and MLflow preferred

Internal

5 Recommendation Analytical Skills

Experience in use cases which includes one or more of

ProductSKU recommendation

Purchasecustomer affinity

Basket or association analysis

Personalisation

Demandorder prediction

Retail or transactional analytics

6 Preferred Experience

3 years of experience

B2B ordering or distributorretailer analytics

Product recommendation or demandorder prediction

Largescale transactional datasets

Databricksbased ML projects

7 Engagement Structure

Duration 3months with optional to extend if required

External Specialist Focus Feature Engineering ML Model Development Recommendation Engine