Senior Manager – Predictive Analytics & Forecasting

OVERVIEW                                                                                

NEOM is an accelerator of human progress and a vision of what a new future might look like. A region in northwest Saudi Arabia on the Red Sea, NEOM is being built from the ground up to include hyperconnected, cognitive cities, ports, next-generation infrastructure and industries, enterprise zones, research centers, sports and entertainment venues and tourist destinations.

As a destination, it will be a home for people who dream big and want to be part of building a new model for exceptional livability, creating thriving businesses and reinventing environmental conservation.

As a workplace, it is a place for people who share our core values of care, curiosity, diversity, passion, respect, and becoming a catalyst for change.

Are you ready to help NEOM find solutions to the world’s most pressing challenges? Are you prepared to create a lasting legacy that benefits generations to come? Then we want to hear from you!

ROLE OVERVIEW

Predictive Analytics and Forecasting Senior Manager in the Economics, Data, and Statistics department will contribute to critical projects focused on forecasting, data analysis, and reporting. In this role, you will design, develop, and maintain forecasting models, with a strong emphasis on demographic forecasting to predict population trends, migration patterns, and other key metrics that inform strategic planning and decision-making.

they will collaborate closely with data scientists, statisticians, and domain experts to prepare, clean, and organize data for modeling purposes. their work will involve conducting advanced analytics, applying statistical and machine learning techniques, and generating insights that support the department’s strategic goals. Additionally, you will evaluate and refine forecasting models to improve their accuracy and applicability across various scenarios.

This position offers the opportunity to develop advanced skills in predictive analytics and forecasting while gaining exposure to cutting-edge tools and methodologies. By contributing to the successful execution of departmental objectives, you will play a vital role in ensuring accurate projections and insights that drive data-informed decision-making.

This role is ideal for individuals who are analytical, detail-oriented, and passionate about building robust forecasting models to address complex challenges, particularly in demographic forecasting. You will thrive in a collaborative environment that encourages innovation and continuous learning.

ROLE COMPETENCIES & ACTIVITIES

The responsibilities will include, but are not limited to:

Data Preparation for Forecasting Models

• Collect, clean, and organize datasets specifically for use in predictive analytics and forecasting models.
• Transform raw data into structured formats suitable for statistical analysis and machine learning, ensuring consistency and accuracy.
• Work with diverse data sources, including databases, APIs, and spreadsheets, to prepare data for forecasting applications.
• Use tools such as Python, R, or SQL to preprocess, transform, and validate data for demographic and economic forecasting.
• Optimize data pipelines to ensure efficient model training and deployment.
• Model Development and Forecasting
• Design, develop, and implement forecasting models to predict trends in demographics, migration, economic indicators, and other key areas.
• Apply advanced statistical techniques and machine learning algorithms to create accurate and reliable forecasts.
• Develop demographic forecasting models that account for factors such as population growth, migration patterns, and income levels.
• Regularly evaluate and refine models to ensure high accuracy and adaptability to changing conditions.
• Explore and incorporate innovative methodologies, such as time-series analysis, ensemble models, or neural networks, to improve forecasting capabilities.

Model Testing and Validation

• Validate the accuracy and reliability of forecasting models through rigorous testing and performance evaluation.
• Conduct back-testing using historical or benchmark data to assess model robustness.
• Document assumptions, limitations, and methodologies for transparency and reproducibility.
• Troubleshoot and resolve issues related to model performance, data anomalies, or unexpected outcomes.
• Ensure models meet quality standards and are aligned with organizational objectives.
• Collaboration and Stakeholder Engagement
• Work closely with data engineers, statisticians, and analysts to ensure forecasting models align with project goals and stakeholder needs.
• Collaborate with demographic and economic experts to incorporate domain-specific insights into forecasting models.
• Present forecasts and key findings to stakeholders, translating complex analytics into actionable insights.
• Gather feedback from stakeholders to refine models and ensure they address organizational priorities effectively.

Reporting and Documentation

• Create comprehensive reports and dashboards to communicate forecasting results and insights.
• Document methodologies, data sources, assumptions, and key outcomes for each forecasting project.
• Develop templates and guidelines for standardized reporting across projects.
• Share progress updates on forecasting initiatives with internal teams and leadership.
• Innovation and Continuous Improvement
• Stay updated on the latest advancements in predictive analytics, statistical modeling, and demographic forecasting techniques.
• Explore opportunities to incorporate new tools and technologies, such as machine learning platforms, geospatial analytics, or simulation models.
• Promote a culture of innovation by identifying and implementing best practices in predictive analytics.
• Continuously evaluate and enhance existing forecasting models to improve their accuracy, scalability, and usability.

Culture and Values

• Embrace NEOM’s culture and Values https://www.neom.com/en-us/about.
• Act with honesty and integrity by following best practices, and upholding the robust standards and expectations set out in NEOM’s Code of Conduct.
• Maintain fair, ethical and professional work practices in accordance with NEOM’s Values and Code of Conduct.
• Adhere to NEOM’s Policies, procedures, and controls to ensure compliance with rules. 

EXPERIENCE & QUALIFICATIONS

Knowledge, Skills, and Experience

• 10+ years of proven experience in designing, developing, and maintaining predictive models, with a focus on forecasting, particularly in demographic and economic domains.
• Proven experience in designing, developing, and maintaining predictive models, with a focus on forecasting, particularly in demographic and economic domains.
• Strong skills in data preparation, cleaning, and transformation for predictive modeling using tools such as Python, R, SQL, or other relevant software.
• Hands-on experience in developing and deploying forecasting models using advanced statistical techniques, machine learning algorithms, and time-series analysis.
• Proficiency in using data visualization tools like Tableau, Power BI, or Shiny to communicate predictive insights effectively.
• Strong understanding of statistical concepts, forecasting methodologies, and best practices for predictive analytics.
• Familiarity with integrating forecasting models with diverse data sources, including databases, APIs, and cloud-based platforms.
• Basic knowledge of big data platforms and tools (e.g., Spark, Hadoop) is a plus.
• Experience with geospatial analytics or incorporating geographic data into demographic forecasting models is advantageous.
• Excellent problem-solving skills with a proven ability to troubleshoot and improve forecasting models.

Qualifications

• Bachelor’s degree in Statistics, Data Science, Computer Science, Economics, Business Analytics, or a related field.
• Advanced degree (Master’s or Ph.D.) in a relevant discipline is highly desirable.
• Demonstrated experience in predictive analytics, forecasting, and related fields, with a strong portfolio showcasing forecasting models or projects.
• Certifications in data science, machine learning, or analytics (e.g., Google Data Analytics, Microsoft Certified: Data Scientist, or equivalent) are a plus.
• Advanced coursework or certifications in statistical modeling, machine learning, or forecasting techniques are preferred.
• Familiarity with agile project management methodologies is advantageous.