data analyst

senior data analyst

senior data scientist

data engineer

data scientist i

data scientist

<div>
 
 
 
 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 www.dar.com.
 
 
 
 
 
 
 Our Vision and Values:
 
 
 
 
 
 
 We aspire to be the chosen home of those with a gift for crafting solutions that empower people and an unwavering passion for learning and innovation. Our core values shape our culture and guide our decision-making. We are committed to:
 
 
 
 
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 Excellence
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 Responsibility
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 Empowerment
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 Connectivity
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 Courage
 </li>
 </ul>
 
 
 
 
 J
 
 
 Job Purpose:
 
 
 
 
 
 
 
 The role of a Data Scientist at Dar will be to extract actionable insights from databases and large, complex datasets to improve design decisions, optimize processes, and enhance project performance. They leverage statistical analysis, machine learning, and predictive modeling and analysis to support data-driven strategies across the project lifecycle.
 
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 
 
 <ul>
 <li>
 Collect, clean, and analyze structured and unstructured data from design, construction, and operational sources.
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 Extract features from multi-formats data sources
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 Develop predictive models for project scheduling, cost estimation, risk assessment, and resource optimization.
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 Visualize data and communicate insights through dashboards, reports, and presentations.
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 Collaborate with engineers, architects, and project managers to translate business needs into data-driven solutions.
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 Evaluate and implement advanced analytics techniques such as machine learning, NLP, and time-series forecasting.
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 Ensure data quality, governance, and compliance within AEC data systems.
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 Research and apply emerging data science tools and methods to AEC industry.
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 </ul>
 
 
 
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 Values Alignment
 
 
 
 (Expected behaviors that reflect Dar&rsquo;s values, tailored to the level and responsibilities of the role.)
 
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 Demonstrates analytical thinking, independence in execution, professionalism, transparency, communication, and accountability in delivering quality outcomes while fostering collaboration across teams.
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 </ul>
 
 
 
 
 
 Requirements:
 
 
 
 
 
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 Bachelor&rsquo;s or Master&rsquo;s in Data Science, Statistics, Computer Science, or a related field.
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 Strong proficiency in Python and SQL and experience with data analysis libraries (Pandas, NumPy, Scikit-learn), and data visualization tools (Power BI),
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 Experience using LLMs for multi-format documents processing
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 Experience working with RDBMS (e.g. PostgreSQL, Microsoft SQL Server) and cloud platforms (AWS, Azure, or GCP).
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 Experience working with machine learning algorithms, statistical modeling
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 Experience in data pipeline development is a plus.
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 Excellent analytical thinking, problem-solving, and communication skills.
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 Familiarity with AEC data formats and tools (e.g., BIM) is a plus.
 </li>
 </ul>
 
 
 
 
 
 
 Kind Note
 
 :
 
 
 
 
 
 
 
 * 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.
 
 
</div>

Data Scientist

INDOS (Garment IO)

<div>
 
 We are hiring a Data Scientist who will focus on delivering high-impact product initiatives while strengthening our core platform .This role offers hands-on exposure to real production challenges and the opportunity to directly impact long-term growth, reliability, and innovation.
 
 
 
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 Design and implement optimization and ML models to solve business problems
 
 
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 Train, evaluate, and continuously improve models using production feedback
 
 
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 Deploy models as scalable services or pipelines
 
 
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 Collaborate with backend teams to integrate models into core systems
 
 
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 Ensure solutions are robust, explainable, and maintainable
 
 
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 </ul>
 <ul>
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 Define and monitor model performance and business impact metrics
 
 
 
 
 
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 </ul>
 Requirements
 
 
 <ul>
 <li>
 
 3+ years of hands-on experience in data science, applied machine learning, or optimization
 
 
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 Strong background in mathematical modeling, optimization, or operations research
 
 
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 Experience with linear, integer, and mixed-integer programming
 
 
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 Knowledge of constraint-based optimization and heuristics/meta heuristics
 
 
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 Proven experience training, validating, and tuning models
 
 
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 Proficient in Python for data science and modeling
 
 
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 Hands-on experience with libraries such as NumPy, Pandas, SciPy, and OR tools (Pyomo, OR-Tools, PuLP, Gurobi, CPLEX)
 
 
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 Familiarity with ML frameworks (scikit-learn, PyTorch, TensorFlow)
 
 
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 Ability to translate business problems into mathematical or statistical models
 
 
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 Experience deploying models to production (APIs, batch jobs, pipelines)
 
 
 
 
 
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 </ul>
 Benefits
 
 
 
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 Social insurance
 
 
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 Medical insurance
 
 
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 Transportation allowance
 
 
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 Hybrid Work Environment
 
 
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 </ul>
</div>

MaxAB

<div>
 
 
 Company Description:
 
 
 
 MaxAB is re-engineering Africa's informal retail sector through a B2B e-commerce and fintech super app. Since launching in 2018, we've connected over 150,000 traditional retailers with suppliers, delivering 2.5+ million orders across Egypt and Morocco. Our fintech business now generates more revenue than e-commerce, with over $180 million in sales last year. Following our merger with Wasoko, we're expanding across Sub-Saharan Africa.
 
 
 
 
 
 
 About the Role:
 
 
 
 MaxAB is seeking a highly skilled
 
 Data Scientist
 
 to join our centralized Data Team. This role focuses on the end-to-end lifecycle of machine learning models moving from initial deployment to production-level fine-tuning and long-term maintenance as well as participating in advanced analytics
 
 
 
 
 
 
 What You&rsquo;ll Do :
 
 
 <ul>
 <li>
 
 Model Deployment &amp; Optimization:
 
 Work on our Computer Vision initiatives, focusing on fine-tuning models to enhance real-time inventory accuracy and agent performance tracking within logistics environments.
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 Automated Decision Engines:
 
 Maintain and refine logic-driven dispatching engines to optimize resource allocation and operational efficiency across multiple markets.
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 </ul>
 
 
 Risk Mitigation &amp; Anomaly Detection
 
 
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 Fraud Detection Systems:
 
 Develop and monitor robust ML models to identify high-risk behaviors and fraudulent patterns within our FinTech and E-commerce platforms.
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 Integrity Maintenance:
 
 Conduct periodic audits and enhancements of existing identity and behavior-matching algorithms to ensure long-term system reliability.
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 </ul>
 
 
 Advanced Product Analytics
 
 
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 Predictive Modeling:
 
 Support the Product team by developing time-series forecasting models to predict market demand and operational trends.
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 Segmentation &amp; Clustering:
 
 Apply unsupervised learning techniques to categorize retailer behaviors, enabling personalized product experiences and targeted risk interventions.
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 </ul>
 
 
 
 
 
 What We&rsquo;re Looking For :
 
 
 <ul>
 <li>
 
 Educational Background:
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, or a related quantitative field.
 </li>
 <li>
 
 Technical Proficiency:
 
 Advanced expertise in
 
 Python
 
 and
 
 SQL
 
 is essential.
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 <li>
 
 Computer Vision:
 
 Practical experience in fine-tuning and deploying CV models (e.g., PyTorch, TensorFlow, OpenCV) in real-world environments.
 </li>
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 Statistical Modeling:
 
 Strong understanding of time-series analysis, clustering techniques, and supervised learning.
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 Deployment Experience:
 
 Familiarity with the transition of models from prototype to production, including monitoring and performance tuning.
 </li>
 </ul>
 
 
 Preferred Skills
 
 
 <ul>
 <li>
 Experience in the
 
 FinTech, E-commerce, or Logistics
 
 sectors.
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 Ability to translate complex technical findings into actionable insights for non-technical stakeholders.
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 </ul>
 
 
</div>

Finaira

<div>The Data Scientist 1 will contribute to the design, development, and deployment of AI and machine learning models to solve specific business problems in the financial sector. Under the guidance of more senior team members, the Data Scientist 1 will participate in data analysis, model building, and communication of findings. This role offers an excellent opportunity to learn and grow within a dynamic team focused on innovative data-driven solutions.
The difference you will make<ul><li>
Develop and implement individual machine learning models for specific banking applications.</li><li>
Conduct focused data exploration and analysis to support model development.</li><li>
Assist in the deployment and testing of machine learning models.</li><li>
Document model development processes and results.</li><li>
Contribute to data preparation and feature engineering.</li></ul>
Requirements<ul><li>
Education: Bachelor&rsquo;s degree in data science, Economics, Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, or a related discipline with excellent academic record.</li><li>
Experience:
</li><li>0-3 years of experience in a data-related role, including internships or academic projects involving data analysis and modeling.</li><li>
Exposure to the financial services industry is a plus.</li><li>
Basic familiarity with AI applications in finance is desirable.</li><li>
Technical Skills:
</li><li>Basic proficiency in at least one of the following languages: Python or R.</li><li>
Basic understanding of machine learning frameworks (scikit-learn, introductory exposure to TensorFlow or PyTorch).</li><li>
Foundational understanding of basic statistical concepts and ML algorithms (Linear/Logistic regression, decision trees).</li><li>
Basic mathematical skills relevant to data analysis.</li><li>
Introductory knowledge of GenAI concepts.</li><li>
Basic proficiency in SQL and database querying.</li><li>
Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, basic use of Tableau or Power BI).</li><li>
Familiarity with cloud computing platforms (AWS, Azure, GCP) is a plus.</li><li>
Basic understanding of working with large data sets.</li></ul> 
<ul><li>
Soft Skills:
</li><li>Strong ownership and accountability for assigned work.</li><li>
Excellent communication, interpersonal, and conflict resolution skills.</li><li>
Effective time management and task prioritization.</li><li>
Analytical thinking and problem-solving skills.</li><li>
Ability to work independently and collaborate with teams within and across functions.</li><li>
Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.</li><li>
Adaptability and learning agility in a fast-paced environment.</li><li>
Strong attention to detail and a commitment to quality.</li><li>
Receptiveness to feedback and continuous improvement mindset.</li></ul></div>

Data Scientist I

<div>
 The Data Scientist 1 will contribute to the design, development, and deployment of AI and machine learning models to solve specific business problems in the financial sector. Under the guidance of more senior team members, the Data Scientist 1 will participate in data analysis, model building, and communication of findings. This role offers an excellent opportunity to learn and grow within a dynamic team focused on innovative data-driven solutions.
 
 
 The difference you will make
 
 
 <ul>
 <li>
 Develop and implement individual machine learning models for specific banking applications.
 </li>
 <li>
 Conduct focused data exploration and analysis to support model development.
 </li>
 <li>
 Assist in the deployment and testing of machine learning models.
 </li>
 <li>
 Document model development processes and results.
 </li>
 <li>
 Contribute to data preparation and feature engineering.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Education: Bachelor's degree in data science, Economics, Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, or a related discipline with excellent academic record.
 </li>
 <li>
 Experience:
 </li>
 <li>
 0-3 years of experience in a data-related role, including internships or academic projects involving data analysis and modeling.
 </li>
 <li>
 Exposure to the financial services industry is a plus.
 </li>
 <li>
 Basic familiarity with AI applications in finance is desirable.
 </li>
 <li>
 Technical Skills:
 </li>
 <li>
 Basic proficiency in at least one of the following languages: Python or R.
 </li>
 <li>
 Basic understanding of machine learning frameworks (scikit-learn, introductory exposure to TensorFlow or PyTorch).
 </li>
 <li>
 Foundational understanding of basic statistical concepts and ML algorithms (Linear/Logistic regression, decision trees).
 </li>
 <li>
 Basic mathematical skills relevant to data analysis.
 </li>
 <li>
 Introductory knowledge of GenAI concepts.
 </li>
 <li>
 Basic proficiency in SQL and database querying.
 </li>
 <li>
 Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, basic use of Tableau or Power BI).
 </li>
 <li>
 Familiarity with cloud computing platforms (AWS, Azure, GCP) is a plus.
 </li>
 <li>
 Basic understanding of working with large data sets.
 </li>
 <li>
 Soft Skills:
 </li>
 <li>
 Strong ownership and accountability for assigned work.
 </li>
 <li>
 Excellent communication, interpersonal, and conflict resolution skills.
 </li>
 <li>
 Effective time management and task prioritization.
 </li>
 <li>
 Analytical thinking and problem-solving skills.
 </li>
 <li>
 Ability to work independently and collaborate with teams within and across functions.
 </li>
 <li>
 Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
 </li>
 <li>
 Adaptability and learning agility in a fast-paced environment.
 </li>
 <li>
 Strong attention to detail and a commitment to quality.
 </li>
 <li>
 Receptiveness to feedback and continuous improvement mindset.
 </li>
 </ul>
</div>

MYLO

<div>mylo is a fintech platform dedicated to helping millions of people and businesses thrive by providing accessible and responsible financial solutions. Whether you&rsquo;re purchasing a mobile phone, a new jacket, a flight ticket, a comfy couch, or even covering school tuition, mylo enables you to buy now and pay later at thousands of points of sale across Egypt. Born out of B.TECH&mdash;Egypt&rsquo;s leading electronics and appliances retailer with over 27 years of experience in offering buy now, pay later solutions&mdash;mylo brings a legacy of trust and innovation to the fintech space. All mylo products are fully Sharia-compliant, ensuring ethical and inclusive financial practices.
We are looking for a Junior Data Scientist with a strong engineering mindset who is eager to evolve beyond &quot;notebook data science.&quot; In this role, you will work across the full consumer finance lifecycle&mdash;analyzing data for Growth, Pricing, and Risk&mdash;while being trained on a modern, high-performance MLOps stack. You will learn to treat data science code as production software.
Responsibilities:<ul>
<li>
End-to-End Modeling: Assist in training and tuning models for various business domains using modern Python libraries.</li>
<li>Engineering Integration: Work with the team to expose models via APIs. You will learn to implement Feature Store definitions and ensure data quality for real-time serving.</li>
<li>Data Operations: Handle data preparation and analysis using SQL and Python. Learn to manage datasets using Data Version Control tools to keep track of changes.</li>
<li>Code Quality: Write clean, modular, and tested code. You will participate in code reviews and use version control (Git) as part of your daily workflow.</li>
<li>Continuous Learning: Participate in our induction program to master our specific tools for model serving, package management, and system monitoring.</li>
</ul>
Requirements<ul>
<li>
Education: B.Sc. in Computer Science / Engineering, Statistics, Mathematics, or a relevant quantitative field.</li>
<li>Technical ML Foundation:</li>
<li><ul><li>Algorithms: Solid conceptual and practical understanding of Classification (Logistic Regression, Decision Trees, Random Forests) and Regression analysis.</li>
<li>Deep Learning: Basic understanding of Neural Networks architectures and principles (e.g., activation functions, loss functions, backpropagation).</li>
<li>Libraries: Hands-on familiarity with Scikit-Learn for preprocessing, model selection, and pipelines.</li>
<li>Optimization: Exposure to hyperparameter tuning concepts and gradient boosting frameworks (e.g., LightGBM or XGBoost).</li>
</ul></li><li>Software Engineering Fundamentals:</li>
<li><ul><li>Version Control: Strong familiarity with Git commands (branching, merging, resolving conflicts) and collaboration platforms (GitHub/GitLab).</li>
<li>Code Quality: Ability to write clean, reusable, and readable code (not just scripts). Understanding of functions, modularity, and basic testing.</li>
</ul></li><li>Core Skills: Strong grasp of Python programming and SQL.</li>
<li>Analytical Foundation: Solid understanding of statistics and standard data manipulation libraries (Pandas, NumPy).</li></ul></div>

Junior Data Scientist

<div>mylo is a fintech platform dedicated to helping millions of people and businesses thrive by providing accessible and responsible financial solutions. Whether you&rsquo;re purchasing a mobile phone, a new jacket, a flight ticket, a comfy couch, or even covering school tuition, mylo enables you to buy now and pay later at thousands of points of sale across Egypt. Born out of B.TECH&mdash;Egypt&rsquo;s leading electronics and appliances retailer with over 27 years of experience in offering buy now, pay later solutions&mdash;mylo brings a legacy of trust and innovation to the fintech space. All mylo products are fully Sharia-compliant, ensuring ethical and inclusive financial practices.
The Role We are looking for a Staff Data Scientist to lead the technical strategy for our decisioning engines. You will operate at the intersection of Data Science and Software Engineering, designing high-scale systems that power multiple business lines&mdash;from Growth &amp; Pricing to Underwriting &amp; Collections. You will move beyond simple model building to architecting robust, reproducible MLOps pipelines that serve real-time financial decisions.
Responsibilities<ul>
<li>
Multi-Domain Technical Strategy: Lead the development of ML solutions across diverse contexts, ensuring that models for Credit Risk, Pricing Elasticity, and Collection Optimization utilize shared infrastructure efficiently.</li>
<li>MLOps Architecture: Champion the adoption of modern Model Serving frameworks and Feature Stores. Design workflows that ensure feature consistency between training and real-time inference.</li>
<li>Engineering Standards: Establish rigorous standards for Data Versioning, experiment tracking, and Hyperparameter Optimization, ensuring all research is reproducible and production-ready.</li>
<li>Production Deployment: Oversee the transition of models from notebook environments to low-latency production APIs. Ensure models are wrapped, containerized, and integrated seamlessly with backend services.</li>
<li>Mentorship: Guide the team in best practices for Python software engineering, including testing strategies, code structure, and performance optimization.</li>
</ul>
Requirements
Requirements<ul>
<li>
Experience: 7+ years in Data Science with a strong emphasis on production engineering. Experience in Fintech, Lending, or Risk is highly preferred.</li>
<li>ML Proficiency: Deep understanding of both classical machine learning (Gradient Boosting, Statistical Models) and Deep Learning frameworks.</li>
<li>Production Engineering: Proven track record of deploying models in real-time environments. Familiarity with the concepts of Feature Stores and Model Registries is essential.</li>
<li>Technical Stack: Expert-level Python skills. Strong proficiency in SQL and relational database design.</li>
<li>Strategic Thinking: Ability to translate complex business KPIs (e.g., reducing Non-Performing Loans) into technical ML roadmaps.</li></ul></div>

Staff Data Scientist

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