Senior Applied Scientist, Commerce Decisioning

Mollkom; Riyadh; Hybrid; SAR 120,000 - 260,000; Full time

Job summary

Mollkom is seeking a data-centric professional to frame ranking and recommendation problems around concrete business needs. You will design A/B tests and causal analyses, connecting commercial outcomes with cost, quality and operational sustainability.

Collaborating with product and engineering, you will translate findings into interpretable decisions that drive performance and impact. The role requires clear communication of data limitations to both technical and commercial teams.

Qualifications

• Applied statistics, machine learning or data science experience.
• Strong Python, SQL, experimental design and uncertainty analysis.
• Understanding of confounding, selection bias and attribution limits.
• Ability to communicate with technical and commercial teams without hiding data limitations.

Responsibilities

• Frame ranking, recommendation and decisioning problems around concrete business needs.
• Design A/B tests and causal analysis where data and experimental design support it.
• Connect commercial outcomes with cost, quality and operational sustainability.
• Partner with product and engineering to turn findings into interpretable, reviewable decisions.

Skills

Statistics/ML

Python

SQL

Experimental design

Uncertainty analysis

Job description

Improving one metric does not explain the whole commercial effect. Work on decisioning, recommendations and experimentation while considering acquisition cost, margin, customer experience and data availability.

Responsibilities

• Frame ranking, recommendation and decisioning problems around concrete business needs.
• Design A/B tests and causal analysis where data and experimental design support it.
• Connect commercial outcomes with cost, quality and operational sustainability.
• Partner with product and engineering to turn findings into interpretable, reviewable decisions.

Qualifications

• Applied statistics, machine learning or data science experience.
• Strong Python, SQL, experimental design and uncertainty analysis.
• Understanding of confounding, selection bias and attribution limits.
• Ability to communicate with technical and commercial teams without hiding data limitations.

Hybrid in Riyadh, Saudi Arabia.