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United Imaging Intelligence

<div>
 <p>
  <strong>
   Job Description
  </strong>
 </p>
 <p>
  We are seeking a motivated AI Product Specialist to join our team. In this role, you will be responsible for understanding our AI products and their market landscape, and supporting sales and marketing initiatives. You will play a crucial role in communicating with customers, providing training, and ensuring successful product deployment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <p>
  1.
  <strong>
   Product Knowledge and Strategy Development
  </strong>
 </p>
 <ul>
  <li>
   Gain a comprehensive understanding of our AI products, including their selling points, market positioning, and competitor strategies.
  </li>
  <li>
   Assist in the formulation of market strategies and the creation of promotional materials for designated regions.
  </li>
 </ul>
 <p>
  2.
  <strong>
   Market Research
  </strong>
 </p>
 <ul>
  <li>
   Conduct thorough market research within assigned regions, focusing on clinical workflows, competitor features, market pricing, and business models.
  </li>
 </ul>
 <p>
  3.
  <strong>
   Customer Communication and Sales Support
  </strong>
 </p>
 <ul>
  <li>
   Engage with customers to understand their needs and provide tailored product recommendations.
  </li>
  <li>
   Collaborate with the sales team to prepare bid documents for tenders and achieve sales targets.
  </li>
 </ul>
 <p>
  4.
  <strong>
   Marketing Activities and Presentations
  </strong>
 </p>
 <ul>
  <li>
   Support various marketing initiatives by creating relevant materials based on customer and medical expert requirements.
  </li>
  <li>
   Conduct professional presentations to effectively communicate product benefits.
  </li>
 </ul>
 <p>
  5.
  <strong>
   Training and Development
  </strong>
 </p>
 <ul>
  <li>
   Provide product training to users, including on-site training sessions.
  </li>
  <li>
   Regularly conduct internal and external training for team members.
  </li>
 </ul>
 <p>
  6.
  <strong>
   Product Deployment Coordination
  </strong>
 </p>
 <ul>
  <li>
   Coordinate and support the deployment of software products to users, developing and implementing effective deployment plans.
  </li>
  <li>
   Evaluate deployment results and provide timely feedback for continuous improvement.
  </li>
 </ul>
 <p>
  7.
  <strong>
   Customer Relationship Management
  </strong>
 </p>
 <ul>
  <li>
   Assist in maintaining strong customer relationships by effectively resolving on-site technical issues.
  </li>
  <li>
   Analyze and organize customer needs to promote product usage.
  </li>
 </ul>
 <p>
  8.
  <strong>
   User Feedback and Product Iteration
  </strong>
 </p>
 <ul>
  <li>
   Collect and relay user issues to the development team to assist in product iteration and enhancement.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <p>
  1.
  <strong>
   Education
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree or higher in Biomedical Engineering, Medical Imaging, Clinical Medicine, Electronic Engineering, Computer Science, or a related field.
  </li>
 </ul>
 <p>
  2.
  <strong>
   Experience
  </strong>
 </p>
 <ul>
  <li>
   Previous work experience in medical imaging, medical devices, or healthcare information systems is preferred.
  </li>
 </ul>
 <p>
  3.
  <strong>
   Skills
  </strong>
 </p>
 <ul>
  <li>
   Excellent communication skills with a strong sense of responsibility and self-motivation.
  </li>
  <li>
   Strong logical analysis and problem-solving abilities.
  </li>
  <li>
   Proficiency in using Office software for product and data presentations.
  </li>
 </ul>
 <p>
  4.
  <strong>
   Travel
  </strong>
 </p>
 <ul>
  <li>
   Willingness and ability to travel as required
  </li>
 </ul>
 <p>
 </p>
</div>


AI Product Specialist

MA'ADEN

<div><div><div><div><div><p><b>Role Purpose:
</b></p><p>The Lead Specialist, Data Science &amp; Analytics, acts as a technical leader and senior practitioner, driving development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across Maaden.
</p><p>The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.
</p><p>Lead Specialist, Data Science &amp; Analytics is to analyze data, extract insights, and build predictive models that help organizations make smarter decisions and solve difficult problems. By blending expertise in statistics, computer science, and business strategy, they not only analyze complex datasets but also build predictive models that improve operations and shape long-term decisions. With nearly every industry leaning on data today, the demand for skilled professionals continues to grow.
</p><p>1. <b>Lead End-to-End Data Science Delivery
</b></p><ul><li><p>Developing, implementing and maintaining databases and data collection systems
</p></li><li><p>Own the full lifecycle of ML/AI initiatives&mdash;from problem framing, data exploration, feature engineering, model development, validation, and MLOps handover.
</p></li><li><p>Deliver scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.
</p></li><li>Performing statistical analysis to understand and interpret data insights
</li><li>Applying data mining techniques to identify patterns, trends, and relationships in large datasets
</li><li>Building predictive models and machine learning algorithms to forecast future outcomes
</li><li>Creating clear data visualizations and reports to communicate findings to stakeholders
</li><li>Working with cross-functional teams to understand business needs and provide data-driven solutions
</li><li>Design and maintain reliable data pipelines and models in partnership with data engineering to ensure data is accurate, timely, and trustworthy for downstream use
</li><li>Ensuring data security and compliance with relevant regulations
</li><li>Staying up to date with latest technological trends and techniques in data science
</li><li><p>Drive experimentation, model versioning, automated retraining, and continuous improvement.<br>
</p></li></ul></div></div><br>
<div><div><p><b>2. Translate Business Needs into AI/Analytics Solutions
</b></p><ul><li><p>Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions
</p></li><li><p>Engage BU/domain stakeholders to identify value creation opportunities and convert them into actionable analytics use cases.
</p></li><li><p>Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data &amp; AI leadership and business teams.<br>
</p></li></ul></div></div><br>
<div><div><p><b>3. Industrialize AI/ML Models (ML Ops &amp; Architecture)
</b></p><ul><li><p>Partner with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.
</p></li><li><p>Set standards for production deployment, testing, monitoring, drift handling, and lifecycle governance.
</p></li><li><p>Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins
</p></li><li><p>Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements<br>
</p></li></ul></div></div><br>
<div><div><p><b>4. Responsible AI, Quality &amp; Governance
</b></p><ul><li>Ensure compliance with Maaden &rsquo;s Responsible AI, data quality, and data governance frameworks.
</li><li>Promote reproducibility, documentation, lineage tracking, and auditability across all data science assets.
</li>Ensure transparency, explainability, and continuous model governance across production and enterprise environments<br>
<li>
</li></ul></div></div><br>
<div></div><div><div><div><b>Minimum Qualifications:
</b></div><p>Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or related fields.<br>
</p><div></div><div><b>Minimum Experience:
</b></div><p>5 &ndash; 8 years&rsquo; experience in Data Science / Advanced Analytics with industrial, mining, or heavy-asset environments preferred. Including at least 2 years leading or mentoring analytics professionals
</p><p>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
</p><p>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS)
</p><p>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.<br>
</p></div></div><br>
<div><div><div><b>Maaden High-Performance Competencies:
</b></div><p><b>Core Competencies
</b></p><ul><li><p><b>Model Accuracy &amp; Reliability: </b>Performance, drift stability, and operational uptime.
</p></li><li><p><b>Adoption &amp; Business Impact: </b>Value realized, user adoption, integration success.
</p></li><li><p><b>Delivery Velocity: </b>Timeliness of development cycles and deployment readiness.
</p></li><li><p><b>Compliance &amp; Quality: </b>Alignment with Responsible AI, governance, and documentation standards.<br>
</p></li></ul></div></div><br>
<div><div><p><b>Skills:
</b></p><ul><li><b>Machine Learning &amp; AI Leadership
</b></li><li><b>Programming Expertise
</b></li><li><b>Generative AI Proficiency
</b></li><li><b>Strong Analytical &amp; Statistical Skills
</b></li><li><b>Business Strategy &amp; Product Thinking
</b></li><li><b>Ethics, Governance &amp; Responsible AI</b></li></ul></div></div></div></div></div><p></p>

Lead Specialist, Data Science & Analytics II

<div><p><b>Job Purpose
</b></p><ul><li><div>The Lead Specialist, Data Science &amp; Analytics, acts as a technical leader and senior practitioner, driving development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across Maaden.
</div></li><li><div>The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.
</div></li><li><div>Lead Specialist, Data Science &amp; Analytics is to analyze data, extract insights, and build predictive models that help organizations make smarter decisions and solve difficult problems. By blending expertise in statistics, computer science, and business strategy, they not only analyze complex datasets but also build predictive models that improve operations and shape long-term decisions. With nearly every industry leaning on data today, the demand for skilled professionals continues to grow<br>
</div></li></ul><p></p><p><b>Key Accountabilities:
</b></p><p><b>1. Lead End-to-End Data Science Delivery
</b></p><ul><li>Developing, implementing and maintaining databases and data collection systems
</li><li>Own the full lifecycle of ML/AI initiatives - from problem framing, data exploration, feature engineering, model development, validation, and MLOps handover.
</li><li>Deliver scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.
</li><li>Performing statistical analysis to understand and interpret data insights
</li><li>Applying data mining techniques to identify patterns, trends, and relationships in large datasets
</li><li>Building predictive models and machine learning algorithms to forecast future outcomes
</li><li>Creating clear data visualizations and reports to communicate findings to stakeholders
</li><li>Working with cross-functional teams to understand business needs and provide data-driven solutions
</li><li>Design and maintain reliable data pipelines and models in partnership with data engineering to ensure data is accurate, timely, and trustworthy for downstream use
</li><li><div>Ensuring data security and compliance with relevant regulations
</div></li><li><div>Drive experimentation, model versioning, automated retraining, and continuous improvement.<br>
</div></li></ul><div></div><p><b>2. Translate Business Needs into AI/Analytics Solutions
</b></p><ul><li><div>Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions
</div></li><li><div>Engage BU/domain stakeholders to identify value creation opportunities and convert them into actionable analytics use cases.
</div></li><li><div>Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data &amp; AI leadership and business teams.<br>
</div></li></ul><p></p><p><b>3. Industrialize AI/ML Models (ML Ops &amp; Architecture)
</b></p><ul><li>Partner with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.
</li><li>Set standards for production deployment, testing, monitoring, drift handling, and lifecycle governance.
</li><li>Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins
</li>Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements<br>
<li>
</li></ul><p></p><p><b>4. Responsible AI, Quality &amp; Governance
</b></p><ul><li>Ensure compliance with Maaden&rsquo;s Responsible AI, data quality, and data governance frameworks.
</li><li>Promote reproducibility, documentation, lineage tracking, and auditability across all data science assets.
</li>Ensure transparency, explainability, and continuous model governance across production and enterprise environments<br>
<li>
</li></ul><p></p><p><b>5. Stakeholder Management &amp; Value Realization
</b></p><ul><li>Communicate insights, results, risks, and recommendations to decision-makers using compelling narratives and visualization.
</li>Track value realization, adoption metrics, and operational impact to ensure measurable benefit.<br>
<li>
</li></ul><p></p><p><b>Minimum Qualification, Experience and Core Competencies:
</b></p><p><b>Minimum Qualifications:
</b></p><ul><li><p>Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or related fields.<br>
</p></li></ul><p></p><p><b>Minimum Experience:<br>
</b><br>
<br>
</p><ul><li><div><b>Minimum Experience:
</b></div></li><li><div>8 &ndash; 10 years&rsquo; experience in Data Science / Advanced Analytics with industrial, mining, or heavy-asset environments preferred. Including at least 2 years leading or mentoring analytics professionals
</div></li><li><div>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
</div></li><li><div>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch , Azure, AWS) &ndash; Microsoft AI Factory
</div></li><li><div>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.<br>
</div></li><li><br>
<b>Machine Learning &amp; Advanced Analytics
</b><ul><li>Hands-on experience developing and deploying <b>machine learning models </b>, including <b>time-series forecasting, predictive modeling, and optimization use cases
</b></li><li>Strong understanding of <b>model performance, validation, stability, and business impact
</b></li></ul></li><li><b>Generative AI &amp; AI Agents
</b><ul><li>Practical experience with <b>Generative AI solutions </b>, including <b>copilots, intelligent automation, and agent-based workflows
</b></li><li>Ability to embed GenAI capabilities into enterprise processes to improve decision-making and operational efficiency
<br>
<br>
Good to Have Capabilities
</li></ul></li><li><b>Data Engineering (IT + OT)
</b><ul><li>Experience designing and maintaining <b>data pipelines </b>across IT and OT environments
</li><li>Exposure to <b>sensor data, streaming / real-time data processing </b>, and industrial data sources
</li><li>Ability to collaborate with data engineering teams to ensure reliable, timely, and trusted data flows
</li></ul></li><li><b>MLOps / AgentOps
</b><ul><li>Experience in <b>model deployment and lifecycle management </b>, including:
<ul><li>Transition from model development to <b>production and scale
</b></li><li>Monitoring, retraining, versioning, and drift management
</li></ul></li><li>Familiarity with automation and operationalization of ML/AI workloads
<br>
<br>
Preferred Experience &amp; Platforms
</li></ul></li><li><b>Cloud &amp; Analytics Platforms
</b><ul><li>Experience working with enterprise cloud platforms, preferably:
<ul><li><b>Microsoft Azure Data Platform
</b></li><li><b>Databricks AI Platform
</b></li><li><b>Microsoft AI Foundry / Microsoft AI Factory
</b></li></ul></li>Understanding of cloud-native architectures for scalable analytics and AI solutions<br>
<li>
</li></ul></li></ul><div></div><p><b>Core Competencies:
</b></p><ul><li><p><b>Model Accuracy &amp; Reliability: </b>Performance, drift stability, and operational uptime.
</p></li><li><p><b>Adoption &amp; Business Impact: </b>Value realized, user adoption, integration success.
</p></li><li><p><b>Delivery Velocity: </b>Timeliness of development cycles and deployment readiness.
</p></li><li><p><b>Compliance &amp; Quality: </b>Alignment with Responsible AI, governance, and documentation standards.</p></li></ul></div><p></p>

Principal Specialist, Data Science & Analytics

<div><div><b>We help the world run better</b><br>
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.</div><p></p><p><b><br>
What you&rsquo;ll build:</b></p><p></p><p><br>
This specialist role sits at the intersection of enterprise SAP delivery and applied AI. You will identify, design, and support the implementation of AI use cases across customer SAP landscapes, from discovery through early deployments, operational adoption, and consumption.</p><p></p><p><b><br>
What you bring:</b></p><p></p><ul><li><p><br>
3&ndash;5 years in enterprise applications, analytics, software engineering, or AI delivery. You have delivered solutions that reached real users, not just prototypes.</p></li><li><p>
Experience contributing to the implementation or activation of AI solutions within enterprise environments.</p></li><li><p>
Comfortable working with business and technical stakeholders in a consulting environment.</p></li><li><p>
Working understanding of AI and ML concepts and how they are applied in enterprise solutions. Familiarity with agent-based AI concepts is a plus.</p></li><li><p>
Experience working with enterprise platforms such as SAP BTP or similar cloud platforms. Exposure to SAP Business AI capabilities is beneficial and will be developed on the job. /</p><p>
Deep SAP platform knowledge is valuable but not the gating factor.</p></li><li><p>
Able to produce clear documentation and contribute to technical discussions.</p></li></ul><p>
What Success Looks Like</p><ul><li><div><ul><li>
AI use cases move beyond experimentation and are adopted in real business workflows.</li><li>
AI capabilities are consumed consistently across relevant business processes.</li><li>
Customer stakeholders re-engage you across subsequent phases of work.</li></ul></div></li></ul><p></p><p><b><br>
Where you belong:</b></p><br>
<p></p><ul><li>
Lead and document AI use case discovery workshops, identifying and prioritizing impactful opportunities for AI within business processes.</li><li>
Prepare clear documentation&mdash;problem statements, value hypotheses, KPIs&mdash;to guide engineering teams and make informed automation decisions.</li><li>
Drive the activation and deployment of AI use cases, collaborating with technical teams to translate concepts into operational solutions, while identifying and resolving adoption barriers.</li><li>
Support the scaling, operational adoption, and ongoing usage of AI capabilities, producing deployment and operations documentation.</li><li>
Contribute to AI solution architecture, creating diagrams, documentation, and ensuring alignment with best practices and responsible AI governance.</li><li>
Advise customers by translating business needs into technical solutions, building trusted relationships, and articulating AI adoption strategies and roadmaps in line with SAP capabilities.</li><li>
Clearly communicate technical concepts to non-technical stakeholders.</li></ul><p></p><p><br>
You will be part of a growing internal AI practice team, collaborating closely with senior architects, AI developers, and data engineers. Senior architects guide complex architecture decisions. Your role is to operate independently within structured delivery contexts and build trusted relationships with customer stakeholders over time.</p><p></p><div><b><br>
Bring out your best</b><br>
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
<br>
<br>
<b>We win with inclusion</b><br>
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.<br>
<br>
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.<br>
<br>
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.<br>
<br>
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.<br>
<br>
Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div><b><br>
AI Usage in the Recruitment Process</b></div><div>
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
</div><p>Please note that any violation of these guidelines may result in disqualification from the hiring process.<br>
<br>
Requisition ID: 448414 | Work Area: Consulting and Professional Services | Expected Travel: 0 - 90% | Career Status: Professional | Employment Type: Limited Full Time | Additional Locations: #LI-Hybrid</p></div>

AI Solution Architect (One-Year Fixed Term contract)

Robusta

<div><p><b>About Octopus by RTG</b></p><p>
Octopus by RTG is the tech hiring and outsourcing arm of <b>Robusta Technology Group</b>, dedicated to connecting exceptional tech talent with top-tier organizations across the <b>MENA, GCC, Europe, the US, and Canada</b>. We specialize in building strong, long-term partnerships between skilled professionals and innovative companies. Our mission is to empower growth, innovation, and excellence by matching the right talent with the right opportunities.</p><p></p><p><b>
About the Role</b></p><p>
We are seeking a highly capable AI Consultant (Manager level or above) to support the Data &amp; AI Lead in establishing and operating an AI Lab / Center of Excellence (CoE) for SAB in Riyadh.</p><b>
Location</b><ul><li>
Based in KSA or willing to relocate
</li><li>On-site presence required in North Riyadh, 5 days per week</li></ul><p></p><p>
The selected candidate will play a key role in driving AI innovation within the organization by supporting the design, development, and deployment of high-impact AI use cases across core banking functions. This includes enabling rapid experimentation, ensuring regulatory compliance, and fostering AI adoption among senior stakeholders.</p><p></p><p><b>
Key Responsibilities</b></p><ul><li>
Support the prioritization and execution of high-value AI use cases across banking domains such as risk, fraud, customer experience, and operations
</li><li>Develop rapid prototypes, proofs of concept (PoCs), and demonstrations, including Arabic-language AI solutions
</li><li>Manage AI lab environments (cloud platforms, GPUs, and sandbox environments) in alignment with internal bank policies
</li><li>Ensure awareness and alignment with KSA regulatory requirements, including SAMA guidelines on data privacy, model governance, and security
</li><li>Facilitate AI ideation workshops and engage senior stakeholders to drive awareness and adoption of AI initiatives
</li><li>Translate complex business challenges into structured AI solutions with clear communication and compelling storytelling
</li><li>Maintain documentation, reporting, and governance processes for AI use cases and thought leadership assets
</li><li>Coordinate with internal teams, external vendors, and technology partners as required</li></ul><br>
<b>
Requirements</b><br>
<ul><li><ul><li>
4&ndash;9 years of experience in AI, data, or technology consulting, preferably within the KSA or GCC banking sector
</li><li>Strong technical literacy, with working knowledge of Python and cloud platforms (preferably GCP)
</li><li>Proven ability to bridge business and technical stakeholders effectively
</li></ul></li></ul><p><b>Nice to Have</b></p><ul><li><ul><li>
Background in data science or applied machine learning
</li><li>Familiarity with modern AI tools and platforms (e.g., Perplexity, Openclaw, Claude)
</li><li>Experience working in MacOS environments</li></ul></li></ul></div>

AI Lab / Center of Excellence Consultant - 6 months - On site - Octopus by RTG

<div><div><b>We help the world run better</b><br>
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.</div><div></div><p><b><br>
What you&rsquo;ll build:</b></p><p>
In this role, you'll turn data into decisions by identifying high-value business problems, framing them analytically, and delivering models and insights that improve customer outcomes and product performance. You'll work across exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning, while partnering closely with product, engineering, sales, operations, or finance stakeholders. Your work will not stop at model accuracy: you'll define success metrics, quantify impact, translate findings into business actions, and help teams prioritize based on value, risk, and feasibility. You&rsquo;ll also contribute to AI-driven analytics using NLP, embeddings, and LLM-assisted workflows for summarization, classification, knowledge extraction, and decision support. The role requires someone who can connect business context with rigorous analysis, explain trade-offs clearly, and influence roadmap decisions with evidence.</p><p><b>
What you bring:</b></p><ul><li>
Strong command of Python and SQL for data extraction, statistical analysis, feature engineering, model development, and analytical automation</li><li>
You have a deep understanding of statistics and probability, including hypothesis testing, experiment design, A/B testing, regression, causal thinking, and interpreting uncertainty</li><li>
You have hands-on experience with a range of machine learning techniques, such as classification, forecasting, clustering, recommendation systems, anomaly detection, and propensity modeling</li><li>
You are skilled at framing business problems into measurable analytical questions, defining success metrics, and connecting model outputs to commercial or operational decisions</li><li>
You excel at building clear data narratives through dashboards, visualizations, presentations, and concise executive communication</li><li>
You demonstrate practical expertise in feature selection, model validation, error analysis, bias identification, and balancing trade-offs between accuracy and usability</li><li>
You have exposure to modern AI approaches, including NLP, generative AI, and LLM-assisted analytics (e.g., semantic search, text classification, summarization, prompt-based analysis)</li><li>
You are experienced with modern analytics and data platforms, such as notebooks, BI tools, cloud data warehouses, Spark, and large-scale data processing environments</li><li>
You have a strong understanding of data quality, lineage, governance, and the discipline required to produce trustworthy and reusable analyses</li></ul><p><b>
About You</b></p><ul><li>
6+ years of data science experience</li><li>
You are curious and bring a structured approach to problem-solving, with the ability to break down complex challenges into clear, actionable steps</li><li>
You are a strong collaborator who enjoys working cross-functionally and influencing decisions through data</li><li>
You are motivated by driving real-world impact, ensuring your analyses and models lead to measurable business outcomes</li><li>
You continuously seek to learn and stay current with evolving data science and AI trends</li></ul><p><b>
Where you belong:</b></p><p>
You will be part of a growing AI and industry expert team dedicated to serving customers across the Kingdom of Saudi Arabia / United Arab Emirates. We are building a collaborative, high‑impact environment that brings together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate, transform, and lead in their markets.</p><p>
This team thrives on working together to turn complex business challenges into practical, scalable solutions. You will find an environment that values curiosity, ownership, and continuous learning, where new ideas are encouraged and real‑world impact matters.This is a place for people who enjoy building something new. You will thrive here if you are customer‑centric, motivated by meaningful outcomes, and comfortable navigating ambiguity in a fast‑evolving AI landscape.</p><p></p><p><b><br>
About the team</b></p><p>
We work closely with decision-makers, challenge assumptions with data, and give data scientists room to influence strategy, not just produce analysis. We value sharp thinking, business curiosity, and clear communication.</p><p></p><div><b><br>
Bring out your best</b><br>
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
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<b>We win with inclusion</b><br>
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.<br>
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SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.<br>
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For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.<br>
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Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.<br>
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Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div><b><br>
AI Usage in the Recruitment Process</b></div><div>
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
</div><p>Please note that any violation of these guidelines may result in disqualification from the hiring process.<br>
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Requisition ID: 450223 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</p></div>

Data Science Expert

MASTER-WORKS

<div><p><b>Job Description:</b></p><p>
The charge of creating and developing intelligent solutions using Artificial Intelligence technologies with a focus on generative AI and data science.
</p><p></p><p>The role entails converting data into useful insights and developing AI powered applications that improve decision making and enhance operational efficiency.</p><p></p><p><b>
Tools &amp; Technologies: </b>Dataiku, Sql server, Power bi, and aws bedrock</p><p></p><p><b>
Key Responsibilities:</b></p><ul><li>
Design, develop, train, and optimize machine learning models for real applications or use cases.</li><li>
Translate business and product requirements into scalable ML/AI solutions.</li><li>
Implement feature engineering, model selection, tuning, and evaluation techniques.</li></ul><ul><li>
Develop, and deploy ML models into production environments with high availability and performance.</li><li>
Build and maintain ML pipelines (training, validation, deployment, monitoring).</li><li>
Monitor model performance, data drift, and model decay; retrain models as needed.</li><li>
Ensure models meet reliability, scalability, and security standards.</li><li>
Work closely with Data Scientists, Product Managers, and Software Engineers.</li><li>
Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.</li><li>
Participate in design and code reviews, ensuring engineering best practices.</li><li>
Optimize models for latency, throughput, and cost.</li><li>
Implement experimentation frameworks (A/B testing, offline evaluation).</li><li>
Apply responsible AI principles, including fairness, explainability, and governance where required.</li></ul><p></p><b><br>
Requirements</b><p><b><br>
Requirements &amp; Qualifications</b>:</p><ul><li>
+4 years of hands-on experience in Machine Learning or applied AI roles.</li><li>
Strong programming skills in Python (and/or Java, Scala).</li><li>
Solid understanding of ML algorithms (supervised, unsupervised, deep learning).</li><li>
Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn.</li><li>
Experience deploying models using Docker, Kubernetes, or cloud ML services.</li><li>
Strong knowledge of data structures, algorithms, and software engineering principles.</li><li>
Experience working in agile, cross-functional teams.</li><li>
Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.</li><li>
Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).</li><li>
Experience with big data technologies (Spark, Kafka, Databricks).</li><li>
Background in NLP, Computer Vision, or Generative AI.</li><li>
Strong problem-solving and analytical thinking</li><li>
Production-first mindset</li><li>
Data-driven decision making</li><li>
High Collaboration and communication skills</li></ul></div>

AI developer

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