Principal Data Scientist

Wasl Group; Dubai; On-site; AED 350,000 - 550,000; Full time

Job summary

Wasl Group seeks a Principal Data Scientist to act as the technical authority for advanced analytics within Property Management. You will lead ML/AI initiatives, translate business priorities into scalable data products, and mentor data science teams across key projects.

You will establish standards for model development, validation, and deployment while driving measurable business value through data-driven insights and strategic recommendations.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Economics, Mathematics, or a related discipline.
• 7–10 years of relevant data science and advanced analytics experience, including 3–5 years in senior technical leadership.
• Strong track record in applied machine learning, predictive analytics, statistical modelling, and delivery of production‑grade data products.
• Experience leading complex data science initiatives across multiple business areas.
• Advanced proficiency in Python, R, SQL, or comparable tools.
• Strong understanding of model validation, data quality, and scalability of analytics solutions.
• Excellent analytical, problem‑solving, stakeholder management, and communication skills.

Responsibilities

• Lead the design, development, validation, and deployment of advanced ML/AI solutions.
• Develop scalable data products aligned with Property Management priorities.
• Translate business requirements into analytical frameworks and measurable data science outputs.
• Establish technical standards for model development, validation, and documentation.
• Monitor KPIs and ensure adoption and business impact of data products.
• Provide technical guidance and mentorship to data science practitioners.

Skills

Statistical Modelling

Predictive Analytics

Data Programming

Business Insights

Data Cleaning

Experimentation

Education

Bachelor's degree

Master's degree

Tools

Python

R

SQL

Jira

Job description

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Position Title: Principal Data Scientist
Reports to: Head - PM Strategy Hub
Department: Property Management

POSITION SUMMARY

The Principal Data Scientist serves as the technical authority for advanced analytics and data science within Property Management, leading the design and deployment of machine learning, AI, and predictive analytics solutions that deliver measurable business value. The role translates strategic business priorities into scalable data products, establishes robust analytical practices, and provides technical leadership and mentorship to data science practitioners across key initiatives.

JOB DIMENSIONS

Number of Staff Supervised

Direct Reports: 0
Total Reports: 0

KEY RESPONSIBILITIES AND PERFORMANCE STANDARDS

Key Accountabilities

• Lead the design, development, validation, and deployment of advanced machine learning, AI, statistical, and predictive analytics solutions.
• Develop scalable data products that address Property Management priorities and support operational and strategic decision-making.
• Translate complex business requirements into analytical frameworks, models, and measurable data science solutions.
• Establish technical standards for model development, validation, coding, documentation, and analytical quality.
• Analyze large and complex datasets to identify patterns, trends, risks, opportunities, and business drivers.
• Integrate analytical models and data products into business processes and existing technology environments.
• Develop reusable, modular, and production-grade analytical code to support scalability and long-term maintainability.
• Translate analytical outputs into clear business insights and recommendations for senior stakeholders.
• Define and monitor KPIs to measure the performance, adoption, and business impact of data products.
• Implement appropriate data and model quality controls to ensure accuracy, reliability, and consistency of analytical outputs.
• Partner with IT, business teams, and other stakeholders to ensure effective deployment and adoption of analytics solutions.
• Champion appropriate data governance, security, privacy, and regulatory requirements in collaboration with IT, Legal, and Compliance.
• Provide technical guidance and mentorship to data scientists and analytics professionals without formal people-management responsibility.
• Evaluate emerging AI, machine learning, and analytics technologies and recommend opportunities for practical application within Property Management.
• Support continuous improvement of analytics methodologies, tools, processes, and delivery practices.

KEY TECHNICAL SKILLS AND KNOWLEDGE

Skill

Description

Proficiency Level

Statistical Analysis & Modelling

Design and validate advanced statistical, machine learning, and AI models for complex business applications.

Advanced

Forecasting & Predictive Analytics

Develop and oversee predictive models and forecasts to support planning and decision-making.

Advanced

Data Tools & Programming

Establish high-quality coding practices and develop scalable solutions using Python, R, SQL, and related technologies.

Advanced

Business Insight Generation

Translate complex analytical findings into strategic, commercially relevant recommendations.

Advanced

Data Collection & Cleaning

Define data preparation, validation, and quality standards for analytical solutions.

Advanced

Design effective approaches for communicating complex insights to business and senior stakeholders.

Advanced

Apply experimentation and testing methodologies to validate analytical hypotheses and business interventions.

Intermediate

COMMUNICATIONS & WORKING RELATIONSHIPS

Internal: Head - PM Strategy Hub, Property Management leadership, IT, Strategic Planning and Analytics, Finance, Asset Management, and other business functions as required.

External: Technology and analytics vendors, service providers, specialist consultants, and other external organizations as required.

WORK SETTING & DECISION AUTHORITY

• Operates as a senior individual functional expert responsible for technically complex and high-impact data science initiatives.
• Exercises significant professional judgment in selecting analytical approaches, methodologies, model architectures, and technical solutions.
• Provides technical recommendations that influence Property Management strategy, operational decisions, and analytics practices.
• Leads complex data science projects and provides technical direction to multidisciplinary project teams without formal line-management responsibility.
• Escalates significant data, technology, governance, or business risks to the Head - PM Strategy Hub.

FINANCIAL RESPONSIBILITIES

• No direct budget ownership.
• Supports evaluation of analytics technology, vendor, and solution requirements to ensure appropriate business value and cost effectiveness.
• Contributes to measurable financial and operational benefits through data-driven optimization, forecasting, and decision support.

SELECTION CRITERIA

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Economics, Mathematics, or a related discipline from a recognized university.
• 7-10 years of relevant data science and advanced analytics experience, including 3-5 years in a senior technical leadership or managerial capacity.
• Strong track record in applied machine learning, predictive analytics, statistical modelling, and delivery of production-grade data products.
• Demonstrated experience leading complex data science initiatives across multiple business areas.
• Advanced proficiency in Python, R, SQL, or comparable analytical and programming technologies.
• Strong understanding of model validation, data quality, scalability, and integration of analytics solutions into business environments.
• Strong business acumen with the ability to translate business problems into analytical solutions and measurable outcomes.
• Excellent analytical, problem-solving, stakeholder management, and communication skills.
• Experience providing technical leadership, coaching, or mentorship to data science professionals.
• Master’s degree in Data Science, Statistics, Computer Science, Engineering, Economics, or a related discipline.
• Experience in real estate, property management, asset management, pricing optimization, or marketing analytics.
• Experience with business intelligence and visualization platforms.
• Experience with Agile delivery methodologies and project management tools such as Jira.
• Exposure to cloud analytics, machine learning platforms, MLOps, or generative AI solutions.