109 Feature Engineering jobs in Saudi Arabia

Overview

Leading the future in luxury electric and mobility

At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.

We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.

Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

Data Analysis Specialist is responsible for all Quality data collection, analysis and visualization, developing and maintaining Quality Dashboards and KPIs.

• Collect and capture all Data and KPIs related to Manufacturing Quality.
• Develop Quality Dashboard using Lucid Applications and Tools to ensure data and KPIs visualization.
• Conduct data analysis and deep dives to visualize priorities and top contributors that require focus.
• Identify data and Quality issues trends versus Problem Solving.
• Track effectiveness of actions plans through data.
• Maintain all Quality Dashboards updated and accurate.
• Escalate urgent issues and prioritize business needs.
• Provide required support to all Quality functions regarding data collection, visualization and analysis.
• Develop regular reports for different management levels.
• Prepare reporting for weekly and monthly Quality reviews.

• Previous experience with OEM is a plus.
• Strong knowledge of MS Office tools (MS-Project, Word, Excel, and PowerPoint)
• Experience with Tableau and SmartSheet is a strong plus.
• Experience with the Manufacturing Execution System Application/Environment is a strong plus.
• Experience with Sales Force Application is a strong plus.
• Detail-oriented with strong record-keeping and organizational skills.
• Excellent written and verbal communication skills and people skills, comfortable presenting ideas and issues to peer groups and leaders.
• Positive energy and attitude.
• Demonstrated ability to work under high demanding level.
• Ability to work in a dynamic, fast-paced environment.

To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to our careers alias or other Lucid Motors employees. Lucid Motors is not responsible for any fees related to unsolicited resumes.

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Job Purpose - الغرض من الوظيفة

The Data Analyst will play a key role in improving the quality of patient safety data at the Saudi Patient Safety Center (SPSC). By applying advanced statistical and analytical methods, the analyst will generate evidence-based reports, develop national patient safety KPIs, and support decision-making at both national and international levels - سيساهم محلل البيانات بدور محوري في تحسين جودة بيانات سلامة المرضى في المركز السعودي لسلامة المرضى ومن خلال تطبيق الأساليب الإحصائية والتحليلية المتقدمة، سيقوم المحلل بإعداد تقارير قائمة على الأدلة، وتطوير مؤشرات أداء وطنية لسلامة المرضى، ودعم عملية اتخاذ القرار على المستويين الوطني والدولي. ويسهم هذا الدور بشكل مباشر في تعزيز مكانة المركز كجهة وطنية رائدة ذات شراكات دولية ومعترف بها من قبل منظمة الصحة العالمية (WHO).

Responsibilities - المسؤوليات

• Collect, clean, analyze, and present findings of healthcare data using advanced statistical tools and methods - جمع البيانات الصحية وتنظيفها وتحليلها وعرض نتائجها باستخدام أدوات وأساليب إحصائية متقدمة.
• Prepare reports highlighting trends, risks, and recommendations for performance improvement - إعداد تقارير تسلط الضوء على الاتجاهات والمخاطر والتوصيات اللازمة لتحسين الأداء.
• Collaborate with clinical teams to interpret findings and implement evidence-based improvements - التعاون مع الفرق السريرية لتفسير النتائج وتطبيق التحسينات المبنية على الأدلة.
• Support research studies and national/international projects related to patient safety - دعم الدراسات البحثية والمشاريع الوطنية والدولية ذات الصلة بسلامة المرضى.
• Develop, monitor, and evaluate patient safety Key Performance Indicators (KPIs) - تطوير ومتابعة وتقييم مؤشرات الأداء الرئيسة (KPIs) الخاصة بسلامة المرضى.
• Ensure accuracy, integrity, and quality assurance of data before reporting - ضمان دقة ونزاهة البيانات وجودتها قبل نشرها أو الإبلاغ عنها.
• Contribute to strengthening SPSC's international reporting and benchmarking in line with WHO standards - الإسهام في تعزيز التقارير الدولية والمقارنات المرجعية للمركز بما يتماشى مع معايير منظمة الصحة العالمية.
• Create dashboards and visualization tools (Power BI/Tableau) to facilitate decision-making in patient safety - إنشاء لوحات متابعة وأدوات عرض بيانية (Power BI/Tableau) لدعم عملية اتخاذ القرار في مجال سلامة المرضى.

Requirement and Qualifications - المتطلبات والمؤهلات

• Bachelor or Master's degree in Biostatistics, Epidemiology, Health Data Science, or a related field - درجة الباكلوريوس او الماجستير في الإحصاء الحيوي، علم الأوبئة، علوم بيانات الصحة، أو مجال ذي صلة.
• Minimum of 4 years' experience in biostatistics or healthcare data analysis, Experience in patient safety data domains is preferred.
• Patient Safety certification - شهادة في سلامة المرضى.
• Certified Professional in Healthcare Quality (CPHQ) - أخصائي معتمد في جودة الرعاية الصحية
• Machine Learning specialization - تخصص في التعلم الآلي.
• Lean Six Sigma Green/Black Belt - لين سقما
• Certified Health Data Analyst (CHDA) - محلل بيانات صحية معتمدة

Skills - المهارات

Technical Skills:

• Proficiency in statistical software and tools such as SAS, R, SPSS, Power BI, or Python - إجادة استخدام البرمجيات والأدوات الإحصائية مثل SAS، R، SPSS، Power BI أو Python.
• Strong SQL and data querying from relational databases or cloud-based environments - إتقان SQL واستخراج البيانات من قواعد البيانات العلائقية أو البيئات السحابية.
• Advanced analytical and problem-solving skills, with ability to extract meaningful insights - مهارات تحليلية متقدمة وحل المشكلات مع القدرة على استنتاج رؤى ذات مغزى.
• Strong reporting skills with ability to communicate complex findings clearly - مهارات قوية في إعداد التقارير وعرض النتائج المعقدة بشكل واضح.
• Ensure data accuracy, quality, and security in compliance with internal policies and data governance standards - ضمان دقة وجودة وأمن البيانات بما يتماشى مع السياسات الداخلية ومعايير حوكمة البيانات.
• Cross-functional Collaboration - القدرة على التعاون الفعال مع فرق متعددة التخصصات.

Soft Skills:

• Strong communication and data presentation abilities for clinical and non-clinical audiences - قدرات تواصل متميزة وعرض البيانات بطريقة مناسبة للجمهور السريري وغير السريري.
• High attention to detail and accuracy in data work - دقة عالية واهتمام بالتفاصيل في العمل مع البيانات.
• Ability to collaborate effectively in multidisciplinary teams - القدرة على التعاون والعمل الجماعي بفعالية.

Job Description

• Collect, clean, and transform structured and unstructured datasets from multiple sources (databases, APIs, data warehouses, and flat files) for analysis.
• Develop, maintain, and optimize SQL queries, stored procedures, and ETL pipelines to ensure reliable data flows.
• Perform statistical analysis, hypothesis testing, and predictive modeling to extract actionable insights and support decision-making.
• Create advanced dashboards and reports using tools such as Power BI, Tableau, or Looker, ensuring KPIs are tracked and visualized effectively.
• Collaborate with data engineers and business stakeholders to define data requirements and ensure alignment between technical outputs and business needs.
• Apply data mining, clustering, and regression techniques to detect patterns, trends, and anomalies across large datasets.
• Document methodologies, maintain reproducibility of analysis, and adhere to best practices for version control and code management (e.g., Git).

Job Requirements

• A degree in computer science, data science or any other relevant field. A master's is a plus
• 4 years of experience in relevant fields
• Data Engineering & Querying: Strong proficiency in SQL
• Visualization & Reporting: Advanced skills in BI tools (Power BI, Tableau, Looker, or equivalent) and ability to design performance-optimized dashboards.
• Data Wrangling: Ability to handle raw, messy data—cleaning, normalizing, feature engineering, and managing large datasets with performance considerations.
• Cloud & Analytics Tools: Familiarity with cloud platforms (GCP BigQuery, AWS Redshift, Azure Synapse) and distributed data systems (Spark, Hadoop) is a plus as well as hands-on experience on Dataiku is a plus.

Direct message the job poster from Saudi Patient Safety Center - المركز السعودي لسلامة المرضى

Job Purpose - الغرض من الوظيفة

The Data Analyst will play a key role in improving the quality of patient safety data at the Saudi Patient Safety Center (SPSC). By applying advanced statistical and analytical methods, the analyst will generate evidence-based reports, develop national patient safety KPIs, and support decision-making at both national and international levels - سيساهم محلل البيانات بدور محوري في تحسين جودة بيانات سلامة المرضى في المركز السعودي لسلامة المرضى ومن خلال تطبيق الأساليب الإحصائية والتحليلية المتقدمة، سيقوم المحلل بإعداد تقارير قائمة على الأدلة، وتطوير مؤشرات أداء وطنية لسلامة المرضى، ودعم عملية اتخاذ القرار على المستويين الوطني والدولي. ويسهم هذا الدور بشكل مباشر في تعزيز مكانة المركز كجهة وطنية رائدة ذات شراكات دولية ومعترف بها من قبل منظمة الصحة العالمية (WHO).

Responsibilities - المسؤوليات

• Collect, clean, analyze, and present findings of healthcare data using advanced statistical tools and methods - جمع البيانات الصحية وتنظيفها وتحليلها وعرض نتائجها باستخدام أدوات وأساليب إحصائية متقدمة.
• Prepare reports highlighting trends, risks, and recommendations for performance improvement - إعداد تقارير تسلط الضوء على الاتجاهات والمخاطر والتوصيات اللازمة لتحسين الأداء.
• Collaborate with clinical teams to interpret findings and implement evidence-based improvements - التعاون مع الفرق السريرية لتفسير النتائج وتطبيق التحسينات المبنية على الأدلة.
• Support research studies and national/international projects related to patient safety - دعم الدراسات البحثية والمشاريع الوطنية والدولية ذات الصلة بسلامة المرضى.
• Develop, monitor, and evaluate patient safety Key Performance Indicators (KPIs) - تطوير ومتابعة وتقييم مؤشرات الأداء الرئيسة (KPIs) الخاصة بسلامة المرضى.
• Ensure accuracy, integrity, and quality assurance of data before reporting - ضمان دقة ونزاهة البيانات وجودتها قبل نشرها أو الإبلاغ عنها.
• Contribute to strengthening SPSC’s international reporting and benchmarking in line with WHO standards - الإسهام في تعزيز التقارير الدولية والمقارنات المرجعية للمركز بما يتماشى مع معايير منظمة الصحة العالمية.
• Create dashboards and visualization tools (Power BI/Tableau) to facilitate decision-making in patient safety - إنشاء لوحات متابعة وأدوات عرض بيانية (Power BI/Tableau) لدعم عملية اتخاذ القرار في مجال سلامة المرضى.

Requirement and Qualifications - المتطلبات والمؤهلات

• Bachelor or Master’s degree in Biostatistics, Epidemiology, Health Data Science, or a related field - درجة الباكلوريوس او الماجستير في الإحصاء الحيوي، علم الأوبئة، علوم بيانات الصحة، أو مجال ذي صلة.
• Patient Safety certification - شهادة في سلامة المرضى.
• Certified Professional in Healthcare Quality (CPHQ) - أخصائي معتمد في جودة الرعاية الصحية
• Machine Learning specialization - تخصص في التعلم الآلي.
• Lean Six Sigma Green/Black Belt - لين سقما
• Certified Health Data Analyst (CHDA) - محلل بيانات صحية معتمدة
• Proficiency in statistical software and tools such as SAS, R, SPSS, Power BI, or Python - إجادة استخدام البرمجيات والأدوات الإحصائية مثل SAS، R، SPSS، Power BI أو Python.
• Strong SQL and data querying from relational databases or cloud-based environments - إتقان SQL واستخراج البيانات من قواعد البيانات العلائقية أو البيئات السحابية.
• Advanced analytical and problem-solving skills, with ability to extract meaningful insights - مهارات تحليلية متقدمة وحل المشكلات مع القدرة على استنتاج رؤى ذات مغزى.
• Strong reporting skills with ability to communicate complex findings clearly - مهارات قوية في إعداد التقارير وعرض النتائج المعقدة بشكل واضح.
• Ensure data accuracy, quality, and security in compliance with internal policies and data governance standards - ضمان دقة وجودة وأمن البيانات بما يتماشى مع السياسات الداخلية ومعايير حوكمة البيانات.
• Cross-functional Collaboration - القدرة على التعاون الفعال مع فرق متعددة التخصصات.
• Strong communication and data presentation abilities for clinical and non-clinical audiences - قدرات تواصل متميزة وعرض البيانات بطريقة مناسبة للجمهور السريري وغير السريري.
• High attention to detail and accuracy in data work - دقة عالية واهتمام بالتفاصيل في العمل مع البيانات.
• Ability to collaborate effectively in multidisciplinary teams - القدرة على التعاون والعمل الجماعي بفعالية.

Referrals increase your chances of interviewing at Saudi Patient Safety Center - المركز السعودي لسلامة المرضى by 2x

Machine Learning & AI Specialist

Location:
Dammam / Remote

Type:
Full-time

Objective:

Develop AI and computer vision solutions for fast and accurate item recognition and counting.

Responsibilities:

• Build and deploy computer vision models for SKU recognition in varied real-world settings.
• Implement 3D perception / Spatial Vision using
  LiDAR
  and other sensors for accurate mapping of items and shelves.
• Optimize models for on-device processing (mobile/tablet) to reduce latency.
• Integrate AI outputs with backend or ERP systems for real-time inventory updates.
• Preprocess, label, and manage datasets for training and testing models.
• Continuously monitor and improve model accuracy and performance.

Required Skills & Tools:

• Deep learning & computer vision (CNNs, 3D CNNs, object detection)
• Frameworks:
  TensorFlow, PyTorch, OpenCV
• On-device inference:
  TensorFlow Lite, ONNX, CoreML
• 3D sensing / LiDAR integration
• Data preprocessing, labeling, and model evaluation

Preferred:

• Augmented Reality (AR) for overlay information
• Self-supervised or semi-supervised learning techniques

1. Build and maintain high-performance microservices using Kotlin and Spring Boot
2. Model relational schemas, optimize SQL queries, and manage data consistency across MySQL and PostgreSQL
3. Collaborate with data scientists to consume ML models (e.g., via REST, gRPC), embed intelligent decisioning into backend services
4. Develop and maintain RESTful APIs; define contracts for frontend, partner services, or AI inference layers
5. Contribute to Docker/Kubernetes-based deployments, CI/CD pipelines, and monitoring (Grafana, Prometheus, etc.)
6. Review code, guide peers on best practices, and participate in architectural discussions and roadmap planning

Skills

• 5+ years of experience building production-ready backend systems
• Expert-level knowledge of Kotlin and Spring Boot ecosystem
• Strong experience with microservices, API design, and distributed systems
• Hands-on experience with MySQL and PostgreSQL including schema design and query optimization
• Solid understanding of software design patterns, RESTful principles, and secure coding practices
• Experience with containerized environments and orchestrators (Docker, Kubernetes)
• Familiarity with integrating AI/ML models (e.g., Python-based APIs, TensorFlow/ONNX serving, or model inference endpoints)
• Strong communication skills and ability to work across engineering and data teams

Roles & Responsibilities:

• Design and implement machine learning models, algorithms, and deep learning applications and systems.
• Optimize and scale ML models for production.
• Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications.
• Monitor model performance and identify differences in data distribution that could potentially affect model performance in real-world applications.
• Ensure algorithms generate accurate user recommendations.
• Prepare and clean data for model training, including data wrangling, feature engineering, and handling missing values.
• Integrate machine learning models into production systems (web applications, APIs) using software engineering best practices.
• Document the machine learning development process and model performance for future reference and collaboration.
• Stay up to date with developments in the machine learning industry.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (preferred).
• At least 5 years of hands-on experience as machine learning engineer or similar role.
• Familiarity with Python, Java, C++, and R.

• Machine Learning Algorithms and Techniques (supervised, unsupervised, reinforcement learning).
• Software Engineering Principles (version control, testing, DevOps).
• Cloud Computing Platforms (AWS, Azure, GCP) (often a plus).
• Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms.
• In-depth knowledge of machine learning frameworks, like Keras or PyTorch.
• Familiarity with data structures, data modeling, and software architecture.
• Excellent time management and organizational skills.

Bachelor’s Degree in Computer Science or related field.

Computer Science fundamentals in object-oriented design, data structures, algorithms and complexity analysis.

• Proficiency in Python.
• Information Retrieval.
• Data Mining.
• Natural language Programming.
• Machine Learning
• Python Data Science stack (NLTK, Pandas, Numpy).
• Proficiency in HTML, Javascript, CSS and general Web 2.0 techniques.
• Experience taking a leading role in building complex software systems that have been successfully delivered to customers.
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.

Interested applicants should send their CVs with mentioning “machine learning specialist” in the subject line.

Roles & Responsibilities:

• Design and implement machine learning models, algorithms, and deep learning applications and systems.
• Optimize and scale ML models for production.
• Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications.
• Monitor model performance and identify differences in data distribution that could potentially affect model performance in real-world applications.
• Ensure algorithms generate accurate user recommendations.
• Prepare and clean data for model training, including data wrangling, feature engineering, and handling missing values.
• Integrate machine learning models into production systems (web applications, APIs) using software engineering best practices.
• Document the machine learning development process and model performance for future reference and collaboration.
• Stay up to date with developments in the machine learning industry.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (preferred).
• At least 5 years of hands-on experience as machine learning engineer or similar role.
• Familiarity with Python, Java, C++, and R.

• Machine Learning Algorithms and Techniques (supervised, unsupervised, reinforcement learning).
• Software Engineering Principles (version control, testing, DevOps).
• Cloud Computing Platforms (AWS, Azure, GCP) (often a plus).
• Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms.
• In-depth knowledge of machine learning frameworks, like Keras or PyTorch.
• Familiarity with data structures, data modeling, and software architecture.
• Excellent time management and organizational skills.