Company Overview:

Dar, the founding member of the Sidara group, is an international multidisciplinary consulting organization specializing in engineering, architecture, planning, environment, project management, facilities management, and economics. Sidara operates in 60 countries with 20,500 professionals, Dar connects people, places, and communities through innovative solutions to the world's most complex challenges. We deliver projects from inception through completion, embracing challenges to empower communities worldwide. Learn more at Dar Al-Handasah and Sidaracollaborative.

Job Overview:

We are seeking a dynamic and experienced Data Scientist to lead our team of Machine Learning (ML) and Artificial Intelligence (AI) engineers. As the leader of our data science team, you will be responsible for driving innovation, overseeing the development of advanced ML/AI models, and leveraging data-driven insights to drive business outcomes.

Responsibilities:

• Lead and manage a team of ML/AI engineers and data scientists.
• Develop and implement strategic initiatives to enhance our data science capabilities.
• Collaborate with cross-functional teams to identify opportunities for leveraging data to drive business solutions.
• Design and implement scalable ML/AI algorithms and models to solve complex business problems.
• Evaluate and deploy cutting-edge ML/AI technologies and tools.
• Ensure compliance with data security and privacy regulations.

Requirements:

• Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• Proven experience (6+ years) leading a team of data scientists and ML/AI engineers in a corporate environment.
• Expertise in developing and deploying ML/AI models in real-world applications.
• Strong programming skills in languages such as Python, R, or Java.
• Good experience in statistical analysis, data mining, and predictive modeling techniques.
• Experience with big data technologies (Hadoop, Spark, etc.) and cloud platforms (AWS, Azure, GCP) is plus
• Excellent communication and leadership skills, with the ability to influence stakeholders and drive strategic decisions based on data-driven insights.
• Ability to thrive in a fast-paced, collaborative environment.

Technical Skills:

1) Statistical Analysis:

• Proficiency in statistical methods to interpret complex data sets.
• Experience with hypothesis testing, regression analysis, time series analysis, and multivariate analysis.
• Ability to use statistical software such as SAS, SPSS, or advanced statistical libraries in Python/R.

2) Data Mining:

• Expertise in data preprocessing, data cleaning, and data transformation techniques.
• Knowledge of clustering, classification, association rule learning, and anomaly detection.
• Experience with data mining tools and frameworks such as RapidMiner, KNIME, or Weka.

3) Computer Vision:

• Experience with image and video processing techniques.
• Proficiency in convolutional neural networks (CNNs) and frameworks like TensorFlow, PyTorch, or OpenCV.
• Knowledge of object detection, image segmentation, and facial recognition technologies.

4) Audio Analysis:

• Familiarity with speech recognition, audio classification, and sound event detection.
• Familiarity with audio analysis tools and libraries such as LibROSA, Kaldi, or Praat.

5) Large Language Models (LLMs):

• Experience with the development, fine-tuning, and deployment of LLMs such as GPT-3/4, BERT, and similar.
• Ability to leverage LLMs for natural language processing tasks, including document analysis, automated reporting, and conversational AI.
• Familiarity with transformer architectures and state-of-the-art NLP techniques.

6) Familiarity with Graph Databases, Vector Databases is a plus

Preferred Qualifications:

• Experience in the Architecture, Engineering and Construction Industry.
• Certification in relevant technologies (e.g., TensorFlow, PyTorch).
• Publications or patents in the field of ML/AI.

* While we carefully review all applications, only candidates meeting the specified requirements will be contacted for further consideration. We appreciate your understanding and thank all applicants for their interest.