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The Firm: Arcsen is a leading global technology consulting firm specializing in providing innovative solutions and expert guidance to businesses across EMEA. With a commitment to excellence, Arcsen partners with industry giants such as Salesforce, MuleSoft, Tableau, Slack, and Sprout, Certinia, and Splunk, ensuring clients receive top-tier services tailored to their unique needs. Position Overview: We are hiring a Sitecore DevOps / Platform Engineer to own CI/CD, environment management and operational readiness for a Sitecore XM Cloud platform. You will stand up the pipelines and environments early so the build team can ship from day one, and you will own performance, hosting/DR posture and release management through go-live and hypercare. Key Responsibilities: Build and maintain CI/CD pipelines using Sitecore CLI and Azure DevOps / Git, with a branching strategy aligned to client IT governance Manage the provided Sitecore environments (non-production and production), including refresh cadence and serialization-based deployments Support the hosting, disaster-recovery and business-continuity posture: backup and restore SLAs, multi-region failover, and 24/7 availability targets Run performance and load benchmarking against the targets (page load, API p95, concurrency, TPS) and feed results back to the team Coordinate edge configuration (Cloudflare Enterprise — WAF, CDN, DDoS, dark-site/crisis mode) with the security team Set up monitoring, centralised logging (log shipping to the client SIEM) and alerting; support incident response during hypercare Document runbooks and lead knowledge-transfer to the client operations team Requirements Bachelor's degree in Computer Science, Information Technology, or related field 4+ years of DevOps / platform engineering Hands-on Azure DevOps and SiteCore CLI / SiteCore Content Serialization Containerisation (Docker / Kubernetes) and CI/CD pipeline design Cloud hosting plus disaster-recovery and backup experience Git branching strategy and release management Nice-to-have Sitecore XM Cloud deployment experience specifically Cloudflare Enterprise (WAF / CDN / DDoS) configuration. IEM / log-shipping experience.Performance and load testing tooling Infrastructure-as-code (Terraform / Bicep) Benefits Hands-on experience with real-world projects and clients Collaborative and supportive work environment Career growth opportunities Arcsen is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Different makes us better. By applying, you give your consent to the processing of your personal data which are necessary to the Personal Data Administrator for the purpose of the recruitment process, and the future recruitment processes. This consent will allow us to contact you in connection with our recruitment. We will process your data for two years. Show more

Role: Senior Data Scientist Location: Egypt, Uzbekistan, and Pakistan (Remote) Work Week: Sunday – Thursday Work Timings: 9:00 AM – 6:00 PM (Saudi Arabian Time Zone) Overview: We’re looking for a Senior Data Scientist to lead the development and deployment of advanced machine learning models that power critical business decisions. In this role, you’ll drive end-to-end ownership of ML solutions, from design and optimization to deployment and monitoring in production environments. You’ll also play a key role in shaping our data science strategy, mentoring junior team members, and ensuring that analytics insights translate into measurable business impact. This is a high-visibility role where your expertise will directly influence product innovation and growth. Role & Responsibilities: Model Development and Optimization: Lead the design, development, and deployment of advanced ML models for complex use cases, such as recommendation systems, fraud detection, customer segmentation, and demand forecasting Partner with data engineers and product teams to ensure models are scalable, reliable, and aligned with business needs Continuously optimize algorithms for performance, accuracy, and efficiency Deployment and Integration: Own end-to-end model deployment processes into production environments using Kubernetes and cloud platforms (AWS, GCP) Define and manage MLOps best practices, including model monitoring, automated retraining, and CI/CD for ML pipelines Champion automation of model training, validation, and deployment workflows to improve system reliability Analytics Strategy & Enablement: Act as a custodian of organizational data, ensuring data quality, consistency, and readiness for advanced analytics and modeling Translate complex data insights into business impact, clearly communicating ROI to stakeholders Drive adoption of analytics and data-driven decision-making across teams by mentoring and enabling business stakeholders Leadership & Collaboration: Mentor junior data scientists and analysts, providing technical guidance and career development support Collaborate closely with engineering and product leadership to shape the company’s data science strategy Stay ahead of emerging AI/ML trends, tools, and research, and advocate for their adoption when relevant Requirements: Proficiency in Python and SQL, with hands-on expertise in ML frameworks such as TensorFlow, PyTorch, Scikit-learn Strong knowledge of deployment tools (Docker, Kubernetes, cloud platforms) and MLOps best practices Proven ability to design and maintain production-grade ML systems Deep understanding of statistical analysis, hypothesis testing, and data visualization Knowledge of cloud-serverless technologies (AWS Lambda, GCP Functions, Azure Functions) Strong familiarity with GCP is a plus Prior experience deploying ML solutions in E-commerce or high-growth environments is highly desirable Familiarity to work with Git and GitHub Dataform is a must Experience: 5+ years in data science, including hands-on ML model development and deployment 3+ years in data analytics, statistical modeling, and experimentation Experience mentoring or leading junior data scientists Exposure to fast-scaling startup or tech environments is a strong plus We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Show more

Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and design appropriate solutions Work closely with IT and infrastructure teams to deploy and maintain data storage and processing systems, including databases, data warehouses, and cloud infrastructure Design, build, and maintain robust, scalable data pipelines to ingest, process, and transform data from various sources, including internal databases and external APIs Optimize data pipelines for performance, scalability, and reliability, ensuring timely and accurate delivery of data Implement data validation and quality checks to identify and rectify any issues in data pipelines, ensuring data integrity Explore and evaluate new technologies, tools, and frameworks to improve data engineering processes and capabilities Perform data modeling and schema design to support analytical and reporting requirements Design and build data marts and business layers to facilitate efficient data access and analysis Requirements Bachelor's degree in Computer Science, Information Systems, or other related technical field or equivalent work Proven experience as a Data engineer or similar role, with at least 4 years of experience Advanced SQL knowledge/experience - complex queries and query optimization Proficiency in programming languages such as Python Experienced in the development of data warehouses and proficient in data modeling Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform Experience in building data streams using technologies such as Kafka, Flink, or Spark Streaming is considered a plus Strong problem-solving skills and attention to detail The ability and willingness to learn new technologies on the job Self driven, highly motivated, fast learner, ambitious and creative Show more

About The Role At Octane, sales are not just about closing deals. The Sales Executive plays a critical role in driving revenue growth and expanding our market presence. As a Sales Executive, you will build strong client relationships, and contribute directly to Octane’s next growth phase. This role combines relationship-building with strategic execution. You will be responsible for managing the full sales cycle while ensuring an exceptional customer experience and achieving revenue targets. You will serve as a trusted advisor to clients, understanding their needs and positioning Octane’s solutions to deliver measurable value. What You'll Be Doing Drive revenue growth by identifying, qualifying, and closing new business opportunities. Manage the full sales cycle: prospecting, outreach, presentations, negotiations, and closing. Build and maintain strong, long-term client relationships. Develop deep understanding of Octane’s products and clearly articulate value propositions. Maintain accurate sales pipeline forecasting and CRM reporting. Achieve and exceed monthly and quarterly sales targets. Gather client feedback and market insights to inform product and commercial strategy. Represent Octane at industry events, meetings, and networking opportunities. Key Areas of Ownership Revenue Growth & Target Achievement Client Acquisition & Relationship Management Pipeline Development & Forecasting Market Intelligence & Competitive Positioning Cross-Functional Collaboration What We're Looking For Bachelor’s degree in business or a related field 3–6 years of experience in B2B sales or account management Proven track record of meeting or exceeding sales targets Strong negotiation, presentation, and communication skills Experience managing the full sales cycle independently CRM proficiency and data-driven sales approach Self-motivated, results-oriented, and highly disciplined Ability to thrive in a fast-paced, growth-focused environment Strong business acumen and customer-first mindset If you’re excited to join a fast-growing company, we’d love to hear from you. Send us your updated resume to hr@octane-tech.io with the subject line "Sales Executive-Giza". Show more

Job Overview: We are seeking a highly skilled and experienced AI team leader to lead our medical imaging AI development team. The successful candidate will be responsible for overseeing the development and implementation of advanced AI algorithms and systems for medical imaging applications. The role demands a combination of technical expertise in AI and machine learning, along with a deep understanding of medical imaging technology and its clinical applications. Key Responsibilities: Leadership and Team Management: Lead and manage a team of AI engineers and data scientists Provide technical guidance and mentorship Foster a collaborative and innovative team environment AI Algorithm Development: Design and implement state-of-the-art AI algorithms for medical imaging Ensure the algorithms meet clinical needs and regulatory standards Stay abreast of the latest developments in AI and medical imaging technology Project Management: Oversee multiple projects from conception to implementation Manage timelines, resources, and budget allocations Ensure projects are completed on time and within specifications Collaboration and Communication: Work closely with medical professionals to understand clinical requirements Liaise with other departments, stakeholders, and external partners Present complex technical details to non-technical audiences Quality Assurance and Compliance: Ensure the highest quality of AI applications Comply with relevant healthcare regulations and standards Implement and maintain data privacy and security measures Qualifications: a Master's or PhD in Computer Science, Artificial Intelligence, Biomedical Engineering, or related field Proven experience in leading AI projects, preferably in the healthcare domain Strong background in machine learning, deep learning, and computer vision Familiarity with medical imaging technologies (e.g., MRI, CT, X-ray) and clinical workflows Experience with regulatory standards in healthcare technology (e.g., HIPAA, FDA) Excellent problem-solving, leadership, and communication skills Skills: Proficiency in programming languages such as Python, C++, or Java Experience with AI and ML frameworks Strong analytical and critical thinking abilities Ability to work in a fast-paced and dynamic environment Powered by JazzHR oQk2ImVOJi Show more

Business insight and decision support: Translate strategic and operational questions into clear analyses, dashboards, reports, and recommendations for leadership and functional teams KPI and metrics ownership: Define, document, and govern business metrics across fuel consumption, transaction activity, customer adoption, fleet performance, station coverage, invoicing, product usage, savings, churn, and operational efficiency Dashboard and reporting delivery: Build reliable self-service dashboards for executives, product, sales, finance, operations, customer success, and country or regional teams Customer and product analytics: Analyze user journeys, feature adoption, customer cohorts, fleet behavior, transaction trends, fuel limits, budget usage, and drop-off points to guide product and growth decisions Operations and finance analytics: Support reconciliation, invoicing, station performance, wallet movement, service usage, cost analysis, revenue tracking, and profitability insights Fraud and anomaly insight: Partner with product, operations, and data engineering to identify unusual fuel patterns, tampering indicators, policy exceptions, and monitoring rules that improve trust and control Experimentation and forecasting: Design analyses for pilots, pricing, campaigns, product launches, and operational changes; support forecasting for consumption, transactions, customer demand, and station utilization Data storytelling: Present insights clearly, explain trade-offs, quantify impact, and convert analysis into practical recommendations and action plans Data quality partnership: Work with data engineering to improve source data, metric definitions, documentation, dashboard reliability, and analytics-ready datasets Analytics mentorship: Set standards for analysis quality, dashboard design, metric governance, and stakeholder communication while mentoring less experienced analysts Requirements Required qualifications 5+ years of experience in data analytics, business intelligence, product analytics, revenue analytics, operations analytics, or a similar analytical role Advanced SQL skills with the ability to independently extract, transform, join, validate, and analyze complex data from multiple domains Strong experience building dashboards and data products using Power BI, Tableau, Looker, Metabase, Superset, or similar BI tools Strong understanding of KPI design, metric definitions, funnel analysis, cohort analysis, segmentation, trend analysis, forecasting, and root-cause analysis Ability to convert ambiguous business questions into analytical plans, structured hypotheses, and actionable recommendations Experience working with transactional, product, customer, payment, operational, or financial datasets at scale Working knowledge of Python or R for analysis, automation, statistical exploration, or notebook-based research Excellent stakeholder management and communication skills, including the ability to explain technical findings to non-technical audiences Strong attention to data accuracy, definitions, documentation, and reproducibility Comfort working in fast-paced product and engineering environments with changing priorities and high ownership expectations Preferred qualifications Experience in fintech, fleet management, logistics, mobility, fuel, marketplace, SaaS, or high-volume transaction businesses Experience with dbt, semantic layers, data catalogs, metric stores, or analytics engineering workflows Familiarity with fraud analytics, anomaly detection, operational controls, pricing analysis, or customer savings measurement Experience with A/B testing, causal inference, retention analysis, churn prediction, LTV modeling, or commercial performance analytics Arabic and English business communication skills are a plus for regional stakeholder engagement Core analytics stack expectations The exact stack may evolve, but the successful candidate should be comfortable operating across the following categories: Analysis: SQL, spreadsheets, Python or R, notebooks, statistical methods, and business case modeling BI and visualization: Power BI, Tableau, Looker, Metabase, Superset, or equivalent dashboarding tools Data modeling: dimensional thinking, metric definitions, cohort tables, funnel tables, and curated analytical datasets Collaboration: requirements gathering, stakeholder workshops, documentation, presentations, and decision memos Governance: metric catalog, dashboard ownership, access control awareness, and data quality issue management Product analytics: event data, customer journeys, feature usage, adoption metrics, retention, and conversion analysis Benefits Competitive salary and benefits package Opportunity to work on cutting-edge technology with a passionate team Career growth and development opportunities A collaborative and inclusive work environment Show more