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About the Role

In this role, you will turn data into decisions by identifying high-value business problems, framing them analytically, and delivering models and insights that improve customer outcomes and product performance. You will work across exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning, while partnering closely with product, engineering, sales, operations, or finance stakeholders. Your work will not stop at model accuracy: you will define success metrics, quantify impact, translate findings into business actions, and help teams prioritize based on value, risk, and feasibility. You’ll also contribute to AI-driven analytics using NLP, embeddings, and LLM-assisted workflows for summarization, classification, knowledge extraction, and decision support. The role requires someone who can connect business context with rigorous analysis, explain trade-offs clearly, and influence roadmap decisions with evidence.

Responsibilities

Identify high-value business problems and frame them analytically.
Deliver models and insights to improve customer outcomes and product performance.
Conduct exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning.
Partner with product, engineering, sales, operations, or finance stakeholders.
Define success metrics and quantify impact.
Translate findings into business actions and help teams prioritize based on value, risk, and feasibility.
Contribute to AI-driven analytics using NLP, embeddings, and LLM-assisted workflows.
Connect business context with rigorous analysis.
Explain trade-offs clearly.
Influence roadmap decisions with evidence.

Requirements

Strong command of Python and SQL for data extraction, statistical analysis, feature engineering, model development, and analytical automation.
Deep understanding of statistics and probability, including hypothesis testing, experiment design, A/B testing, regression, causal thinking, and interpreting uncertainty.
Hands-on experience with a range of machine learning techniques, such as classification, forecasting, clustering, recommendation systems, anomaly detection, and propensity modeling.
Skilled at framing business problems into measurable analytical questions, defining success metrics, and connecting model outputs to commercial or operational decisions.
Excel at building clear data narratives through dashboards, visualizations, presentations, and concise executive communication.
Practical expertise in feature selection, model validation, error analysis, bias identification, and balancing trade-offs between accuracy and usability.
Exposure to modern AI approaches, including NLP, generative AI, and LLM-assisted analytics (e.g., semantic search, text classification, summarization, prompt-based analysis).
Experience with modern analytics and data platforms, such as notebooks, BI tools, cloud data warehouses, Spark, and large-scale data processing environments.
Strong understanding of data quality, lineage, governance, and the discipline required to produce trustworthy and reusable analyses.
6+ years of data science experience.
Curious and bring a structured approach to problem-solving, with the ability to break down complex challenges into clear, actionable steps.
Strong collaborator who enjoys working cross-functionally and influencing decisions through data.
Motivated by driving real-world impact, ensuring analyses and models lead to measurable business outcomes.
Continuously seek to learn and stay current with evolving data science and AI trends.

Skills

Python
SQL
Statistical analysis
Feature engineering
Model development
Analytical automation
Statistics
Probability
Hypothesis testing
Experiment design
A/B testing
Regression
Causal thinking
Machine learning
Classification
Forecasting
Clustering
Recommendation systems
Anomaly detection
Propensity modeling
Data visualization
Executive communication
Feature selection
Model validation
Error analysis
Bias identification
NLP
Generative AI
LLM-assisted analytics
Semantic search
Text classification
Summarization
Prompt-based analysis
Notebooks
BI tools
Cloud data warehouses
Spark
Large-scale data processing
Data quality
Data lineage
Data governance

Location

Kingdom of Saudi Arabia
United Arab Emirates

Work Type

Hybrid
Regular Full Time

Experience Level

6+ years of data science experience
Professional

Benefits

Constant learning
Skill growth
Great benefits
Team that wants you to grow and succeed
Focus on health and well-being
Flexible working models

About the Company

SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively.
Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management.
As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development.
Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves.
At SAP, you can bring out your best.

Equal Opportunity

SAP's culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best.
At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential.
We ultimately believe in unleashing all talent and creating a better world.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities.
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.