Data Scientist / Advanced Analytics Consultant - 0–12+ Years Experience

Data Scientist / Advanced Analytics Consultant (T1–T5)

Riyadh, Kingdom of Saudi Arabia (KSA)

Relocation Required: Yes

0–12+ Years

We are seeking Data Scientists and Advanced Analytics Consultants across multiple experience levels (T1–T5) to deliver advanced analytics, statistical modeling, machine learning, and business intelligence solutions. The successful candidate will transform complex datasets into actionable insights that drive strategic and operational decision-making.

The role covers predictive analytics, customer behavior analysis, product analytics, user journey optimization, digital interface friction analysis, experimentation, and product conversion funnel optimization using modern analytics platforms, visualization tools, and machine learning technologies.

• Apply statistical analysis, predictive modeling, and machine learning techniques to solve business problems.
• Analyze structured and unstructured datasets to identify trends, patterns, and opportunities.
• Design and develop predictive, classification, clustering, and forecasting models.
• Build dashboards and interactive reports to communicate analytical insights.
• Perform user behavior analysis, customer segmentation, churn prediction, and conversion optimization.
• Analyze digital interface friction and customer journeys using product analytics platforms.
• Implement and validate client-side and server-side event tracking strategies.
• Design event taxonomies, data layers, and product analytics instrumentation.
• Develop A/B testing frameworks and measure experiment outcomes.
• Collaborate with business stakeholders, product teams, data engineers, and software developers.
• Validate data quality, statistical assumptions, and model performance.
• Produce clear documentation for analytical models, business insights, and reporting methodologies.
• Follow data governance, privacy, and Responsible AI best practices.

• Python (Pandas and NumPy and SciPy and scikit-learn)
• R

• Databricks or Dataiku

• BigQuery or Snowflake

• Power BI or Tableau or Looker

• Google Analytics 4 (GA4) or Mixpanel or Amplitude

• Client-side Event Tracking
• Server-side Event Tracking
• Data Layer Tag Management
• Product Event Instrumentation

• Regression
• Classification
• Clustering
• Time Series Forecasting
• Statistical Modeling

• SQL
• Data Visualization
• A/B Testing
• Experiment Design
• Customer Analytics
• Product Analytics

Role Focus: Learning, data exploration, and analytical execution under supervision.

• Clean, prepare, and validate datasets for analysis.
• Perform exploratory data analysis (EDA).
• Build basic statistical models and visualizations.
• Assist in dashboard development and report generation.
• Support implementation of product analytics tracking.
• Validate event tagging and data collection accuracy.
• Document analytical findings and model outputs.
• Learn business analytics methodologies and statistical techniques.

Role Focus: Independent analytical delivery.

• Develop predictive and statistical models for business use cases.
• Perform customer segmentation and behavioral analysis.
• Build production-ready dashboards and KPI reporting.
• Implement event tracking strategies using GA4, Mixpanel, or Amplitude.
• Analyze conversion funnels and identify optimization opportunities.
• Perform hypothesis testing and A/B experiment analysis.
• Collaborate with engineering teams to improve data quality.
• Deliver analytical reports and actionable recommendations.

Role Focus: Solution ownership and advanced analytics.

• Design end-to-end advanced analytics and machine learning solutions.
• Lead predictive modeling, forecasting, and optimization initiatives.
• Design product analytics frameworks and event taxonomies.
• Analyze digital interface friction and customer journeys.
• Develop advanced experimentation methodologies.
• Mentor junior data scientists and review analytical deliverables.
• Translate business requirements into analytical solutions.
• Improve analytical model accuracy, scalability, and business impact.

Role Focus: Technical leadership and enterprise analytics delivery.

• Lead enterprise-wide analytics and machine learning initiatives.
• Define analytics architecture, methodologies, and governance standards.
• Design scalable customer analytics and product intelligence solutions.
• Drive advanced experimentation, behavioral analytics, and predictive analytics programs.
• Review analytical models, dashboards, and statistical methodologies.
• Lead stakeholder engagements and translate strategic objectives into analytical roadmaps.
• Mentor cross-functional analytics teams.
• Establish best practices for analytics engineering, visualization, and reporting.

Role Focus: Enterprise analytics strategy, innovation, and architecture.

• Define enterprise data science and advanced analytics strategy.
• Own architecture decisions for large-scale analytics platforms.
• Lead organizational adoption of AI-driven decision intelligence.
• Develop enterprise standards for predictive analytics, experimentation, and statistical governance.
• Drive innovation in customer analytics, behavioral analytics, and digital product optimization.
• Advise executive leadership on analytics strategy and business transformation.
• Evaluate emerging analytics platforms, AI technologies, and data science methodologies.
• Lead enterprise-wide analytics communities, governance forums, and technical strategy initiatives.
• Establish best practices for responsible analytics, data privacy, and model governance.

One or more of the following certifications is highly preferred:

• Google Professional Data Engineer
• Databricks Certified Professional
• Tableau Desktop Certified Professional
• DataCamp or Coursera Data Science Certifications
• Google Analytics Certification
• Mixpanel Certified Professional
• Amplitude Product Analytics Certification
• Equivalent industry-recognized Data Science or Analytics certifications

• Analytical Model Documentation
• Statistical Analysis Reports
• Predictive Models with Performance Metrics
• Business Intelligence Dashboards
• Data Visualization Reports
• User Behavior Tracking Frameworks
• Product Conversion Funnel Analysis
• Digital Interface Friction Analysis Reports
• Cross-Platform Product Event-Tagging Validation Schemas
• Customer Segmentation & Experimentation Reports
• Executive Analytics Presentations

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Artificial Intelligence, Economics, Engineering, or a related field.
• Strong knowledge of statistical modeling, machine learning, predictive analytics, and experimentation techniques.
• Experience with cloud data platforms, product analytics tools, and modern BI solutions.
• Understanding of digital analytics, event instrumentation, customer journey analytics, and conversion optimization.
• Excellent analytical thinking, communication, stakeholder management, and problem-solving skills.
• Ability to work in Agile, cross-functional, and enterprise-scale environments.