data science team lead

ENEC Operations

<div>
 Job Title: Data Science Expert
 <br/>
 <br/>
 Posting Date: 7 Jul 2026
 <br/>
 <br/>
 Requisition ID: 3584
 <br/>
 <br/>
 Location: HQ - Abu Dhabi
 <br/>
 <br/>
 Posting Status: Active Recruitment
 <br/>
 <br/>
 <strong>
  Job Purpose
  <br/>
  <br/>
 </strong>
 The Data Science Expert leads and develops high-performing teams of data scientists and data engineers to deliver advanced analytics, AI, and predictive modeling solutions for ENEC&rsquo;s nuclear operations. This role ensures technical excellence, compliance with nuclear safety standards, and the delivery of actionable insights that optimize plant performance, fuel cycle management, and operational reliability. The Expert acts as a strategic advisor, technical authority, and mentor, driving innovation and embedding analytics into the core of ENEC&rsquo;s mission.
 <br/>
 <br/>
 Key Activities, Responsibility &amp; Accountability
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strategic Leadership:
   <br/>
   <br/>
  </li>
 </ul>
 Drive the data science and analytics strategy for nuclear operations, ensuring alignment with ENEC&rsquo;s safety, reliability, and business objectives.
 <br/>
 <br/>
 <ul>
  <li>
   Technical Excellence:
   <br/>
   <br/>
  </li>
 </ul>
 Oversee the design, development, and deployment of advanced models for reactor performance, fuel cycle optimization, outage prediction, and anomaly detection.
 <br/>
 <br/>
 <ul>
  <li>
   Team Leadership:
   <br/>
   <br/>
  </li>
 </ul>
 Lead, mentor, and develop multidisciplinary teams of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous improvement.
 <br/>
 <br/>
 <ul>
  <li>
   Stakeholder Engagement:
   <br/>
   <br/>
  </li>
 </ul>
 Collaborate with plant, fuel, engineering, and regulatory teams to embed analytics into operational workflows and decision-making.
 <br/>
 <br/>
 <ul>
  <li>
   Governance &amp; Compliance:
   <br/>
   <br/>
  </li>
 </ul>
 Ensure all analytics activities adhere to nuclear safety culture, regulatory requirements, and robust data governance.
 <br/>
 <br/>
 <ul>
  <li>
   Operational Excellence:
   <br/>
   <br/>
  </li>
 </ul>
 Monitor and improve the impact of analytics on plant reliability, fuel efficiency, and business outcomes.
 <br/>
 <br/>
 <ul>
  <li>
   Expert Knowledge Application:
   <br/>
   <br/>
  </li>
 </ul>
 Apply advanced expertise in statistical modeling, machine learning, and AI to develop solutions for complex nuclear analytics challenges, ensuring technical rigor and industry compliance.
 <br/>
 <br/>
 <ul>
  <li>
   Complex Problem Solving:
   <br/>
   <br/>
  </li>
 </ul>
 Lead the resolution of ambiguous and high-impact analytics issues by designing innovative approaches, conducting root cause analysis, and implementing corrective/preventive actions to enhance operational reliability.
 <br/>
 <br/>
 <ul>
  <li>
   Professional Know-How:
   <br/>
   <br/>
  </li>
 </ul>
 Utilize deep technical know-how to architect, validate, and deploy digital twins, predictive maintenance models, and fuel cycle optimization tools, ensuring best practices in MLOps and automation.
 <br/>
 <br/>
 <strong>
  Responsibilities &amp; Accountabilities (contd.)
  <br/>
  <br/>
 </strong>
 Responsibilities and Accountabilities:
 <br/>
 <br/>
 <ul>
  <li>
   Define, communicate, and continuously refine the analytics vision and multi-year roadmap for nuclear operations.
  </li>
  <li>
   Advise executive leadership on leveraging AI and advanced analytics for plant optimization, fuel cycle management, and operational excellence.
  </li>
  <li>
   Lead the development of business cases for analytics investments focused on nuclear plant performance, predictive maintenance, and fuel efficiency.
  </li>
  <li>
   Align analytics initiatives with ENEC&rsquo;s digital transformation, safety culture, and national mission.
  </li>
  <li>
   Monitor industry trends and emerging technologies to ensure ENEC remains at the forefront of nuclear analytics.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Responsibilities And Accountabilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Direct the design, development, and deployment of advanced statistical, machine learning, and AI models for nuclear plant operations, fuel cycle analysis, and safety-critical predictions.
  </li>
  <li>
   Oversee the development and validation of digital twins, predictive maintenance models, and fuel consumption forecasting tools.
  </li>
  <li>
   Ensure all models are validated against nuclear industry standards, regulatory requirements, and plant-specific constraints.
  </li>
  <li>
   Lead the adoption of MLOps best practices for continuous monitoring, retraining, and governance of models deployed in nuclear environments.
  </li>
  <li>
   Drive the adoption of automation, CI/CD pipelines, and advanced monitoring for analytics operations.
  </li>
  <li>
   Lead technical reviews, audits, and assurance activities to maintain high standards of quality, reliability, and compliance.
  </li>
  <li>
   Ensure robust documentation, explainability, and auditability of all models and analytics solutions
   <br/>
   <br/>
  </li>
 </ul>
 Professional Certifications
 <br/>
 <br/>
 Relevant certifications in AI/ML, MLOps, and Data Governance.
 <br/>
 <br/>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 Min - Master&rsquo;s degree in data science, computer science, engineering, or related discipline. Proven experience leading data science teams in regulated environments
 <br/>
 <br/>
 Pref - PhD or equivalent. Experience in nuclear, energy, or highly regulated sectors.
 <br/>
 <br/>
 <strong>
  Experience
  <br/>
  <br/>
 </strong>
 8 years of relevent experience
</div>


Data Science Expert

Venatore

<div><p><b>About Us</b><br>
Venat&ocirc;re is a mission-driven government contractor based in Tampa, FL, supporting federal and civilian agencies with secure cutting-edge technology, cybersecurity, and mission support services. Our teams are trusted in demanding environments because we integrate with client missions, combining technical depth, operational precision, and innovative thinking to deliver meaningful results where they matter most.</p><p><b>
About the Job</b><br>
The Data Scientist Lead is responsible for leading the organization's data science, data engineering, and analytics functions in support of mission-critical military operations. This senior technical leadership role oversees the design, development, and operationalization of advanced data analytics, artificial intelligence, and machine learning capabilities that enhance data-driven decision-making across the command. Working closely with senior government stakeholders, including the Chief Data Officer (CDO) and Executive Data Officer (XDO), the Data Scientist Lead translates operational requirements into scalable technical solutions while providing strategic direction, technical oversight, and mentorship to a multidisciplinary team. This position requires the ability to manage multiple priorities in a dynamic, mission-focused environment and may require occasional domestic and international travel.</p><p><b>
Responsibilities</b></p><p><b>
Leadership &amp; Strategic Oversight</b></p><ul><li>
Lead and provide technical oversight for data engineering, data science, analytics, and predictive analytics teams in support of operational mission objectives.</li><li>
Establish strategic priorities for data management, advanced analytics, AI/ML, and data engineering initiatives.</li><li>
Serve as the senior technical advisor on data science, machine learning, and analytics capabilities.</li><li>
Mentor and develop technical staff while promoting best practices, innovation, and continuous improvement.</li><li>
Manage multiple concurrent projects, priorities, and deliverables in a fast-paced operational environment.</li></ul><p><b>
Data Science &amp; Artificial Intelligence</b></p><ul><li>
Lead the development, validation, deployment, and operationalization of advanced statistical models and AI/ML solutions.</li><li>
Apply supervised, unsupervised, reinforcement learning, and generative AI techniques, including Large Language Models (LLMs) and multimodal AI, to solve complex mission challenges.</li><li>
Guide the full data science lifecycle, including data exploration, feature engineering, model development, validation, deployment, and performance monitoring.</li><li>
Evaluate emerging AI and machine learning technologies for mission applicability and operational effectiveness.</li></ul><p><b>
Data Engineering &amp; Architecture</b></p><ul><li>
Oversee the design, implementation, and maintenance of secure, scalable, and fault-tolerant data pipelines supporting structured and unstructured data.</li><li>
Direct ETL/ELT processes, data integration, data warehousing, and modern data lake/lakehouse architectures.</li><li>
Ensure data quality, governance, accessibility, and compliance throughout the data lifecycle.</li><li>
Support enterprise data management strategies and architecture modernization initiatives.</li></ul><p><b>
Stakeholder Engagement &amp; Mission Support</b></p><ul><li>
Collaborate with the USCENTCOM Chief Data Officer (CDO), Operations Directorate Executive Data Officer (XDO), and other government stakeholders to define operational data requirements.</li><li>
Participate in governance boards, technical working groups, and strategic planning forums.</li><li>
Translate complex technical findings into clear, actionable recommendations for senior military leadership and non-technical stakeholders.</li><li>
Ensure analytical capabilities directly support operational planning, mission execution, and strategic decision-making.</li></ul><p><b>
Analytics &amp; Technology</b></p><ul><li>
Guide the use of SQL, Python, R, and other analytical tools to develop data-driven solutions.</li><li>
Oversee implementation and utilization of visualization platforms such as Power BI, Tableau, Qlik, Palantir Foundry, and Maven Smart System (MSS).</li><li>
Support enterprise analytics platforms, distributed data processing technologies, and database environments including Apache Spark, Databricks, Hadoop, Oracle, PostgreSQL, MySQL, and Microsoft SQL Server.</li><li>
Promote adoption of modern analytics methodologies and industry best practices.</li></ul><p><b>
Required Qualifications</b></p><ul><li>
U.S. Citizenship is required.</li><li>
Active Top Secret security clearance with SCI eligibility.</li><li>
Bachelor's degree in Data Science, Analytics, Computer Science, Information Technology, or a related technical discipline.</li><li>
More than 10 years of progressively responsible experience in data science, analytics, or data engineering, including significant leadership experience.</li><li>
Demonstrated experience supporting Military, Federal Government, or Intelligence Community organizations.</li><li>
Proven experience gathering, implementing, and managing data science requirements for senior government stakeholders.</li><li>
Expertise developing and deploying advanced AI/ML solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li><li>
Advanced proficiency in Python and/or R for data engineering, automation, analytics, and machine learning development.</li><li>
Experience designing and maintaining ETL/ELT pipelines, data warehouses, and data lake/lakehouse environments.</li><li>
Experience with enterprise data visualization and analytics platforms, including Power BI, Tableau, Qlik, Palantir Foundry, or Maven Smart System (MSS).</li><li>
Experience working with distributed data processing technologies such as Apache Spark, Databricks, and Hadoop.</li><li>
Experience administering or utilizing relational database platforms including SQL Server, Oracle, PostgreSQL, and MySQL.</li><li>
Strong written and verbal communication skills with demonstrated experience briefing senior military or government leadership.</li><li>
Ability to travel occasionally to domestic and international locations.</li></ul><p><b>
Preferred Qualifications</b></p><ul><li>
Master's degree in Data Science, Computer Science, Analytics, Information Technology, or another related technical discipline.</li><li>
Experience implementing enterprise data and analytics solutions within Azure, AWS, or Google Cloud environments.</li><li>
Strong knowledge of Department of Defense data strategies, governance frameworks, cybersecurity requirements, and information assurance standards.</li><li>
Experience with ESRI ArcGIS technologies and geospatial analytics.</li><li>
Demonstrated success leading cross-functional technical teams in fast-paced operational environments.</li><li>
Experience supporting AI/ML modernization initiatives within Department of Defense or Intelligence Community organizations.</li></ul><p><b>
Benefits</b><br>
Venat&ocirc;re offers a competitive benefits package designed to support the well-being of our employees, including:</p><ul><li>
Paid Time Off (PTO)</li><li>
10 Federal Holidays</li><li>
401(k) with company matching</li><li>
Medical, dental, and vision insurance</li><li>
Paid military leave</li></ul><p><i>
Venat&ocirc;re is a woman owned small business and an equal opportunity employer. We consider qualified applicants without regard to disability or protected veteran status.</i></p></div>

Data Scientist Lead

Emirates Nuclear Energy

<div></div><div><div><div><div><div>Posting Date: 7 Jul 2026
</div></div></div></div><div><div><div><div>Requisition ID: 3584
</div></div></div></div><div><div><div><div>Location: HQ - Abu Dhabi
</div></div></div></div><div><div><div><div>Posting Status: Active Recruitment
</div></div></div></div><div><div><div><div><div><div><div><h2 class="jobSectionHeader"><b>Job Purpose</b></h2>
</div><div><p>The Data Science Expert leads and develops high-performing teams of data scientists and data engineers to deliver advanced analytics, AI, and predictive modeling solutions for ENEC&rsquo;s nuclear operations. This role ensures technical excellence, compliance with nuclear safety standards, and the delivery of actionable insights that optimize plant performance, fuel cycle management, and operational reliability. The Expert acts as a strategic advisor, technical authority, and mentor, driving innovation and embedding analytics into the core of ENEC&rsquo;s mission.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Key Activities, Responsibility &amp; Accountability</b></h2>
</div><div><div>Responsibilities
<br>
<ul><li>Strategic Leadership:
</li></ul>Drive the data science and analytics strategy for nuclear operations, ensuring alignment with ENEC&rsquo;s safety, reliability, and business objectives.
<br>
<ul><li>Technical Excellence:
</li></ul>Oversee the design, development, and deployment of advanced models for reactor performance, fuel cycle optimization, outage prediction, and anomaly detection.
<br>
<ul><li>Team Leadership:
</li></ul>Lead, mentor, and develop multidisciplinary teams of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous improvement.
<br>
<ul><li>Stakeholder Engagement:
</li></ul>Collaborate with plant, fuel, engineering, and regulatory teams to embed analytics into operational workflows and decision-making.
<br>
<ul><li>Governance &amp; Compliance:
</li></ul>Ensure all analytics activities adhere to nuclear safety culture, regulatory requirements, and robust data governance.
<br>
<ul><li>Operational Excellence:
</li></ul>Monitor and improve the impact of analytics on plant reliability, fuel efficiency, and business outcomes.
<br>
<ul><li>Expert Knowledge Application:
</li></ul>Apply advanced expertise in statistical modeling, machine learning, and AI to develop solutions for complex nuclear analytics challenges, ensuring technical rigor and industry compliance.
<br>
<ul><li>Complex Problem Solving:
</li></ul>Lead the resolution of ambiguous and high-impact analytics issues by designing innovative approaches, conducting root cause analysis, and implementing corrective/preventive actions to enhance operational reliability.
<br>
<ul><li>Professional Know-How:
</li></ul>Utilize deep technical know-how to architect, validate, and deploy digital twins, predictive maintenance models, and fuel cycle optimization tools, ensuring best practices in MLOps and automation.</div>
</div></div><div><div><h2 class="jobSectionHeader"><b>Responsibilities &amp; Accountabilities (contd.)</b></h2>
</div><div><p>Responsibilities and Accountabilities:</p>
<ul><li>Define, communicate, and continuously refine the analytics vision and multi-year roadmap for nuclear operations.
</li><li>Advise executive leadership on leveraging AI and advanced analytics for plant optimization, fuel cycle management, and operational excellence.
</li><li>Lead the development of business cases for analytics investments focused on nuclear plant performance, predictive maintenance, and fuel efficiency.
</li><li>Align analytics initiatives with ENEC&rsquo;s digital transformation, safety culture, and national mission.
</li><li>Monitor industry trends and emerging technologies to ensure ENEC remains at the forefront of nuclear analytics.
</li></ul>Responsibilities and Accountabilities:
<ul><li>Direct the design, development, and deployment of advanced statistical, machine learning, and AI models for nuclear plant operations, fuel cycle analysis, and safety-critical predictions.
</li><li>Oversee the development and validation of digital twins, predictive maintenance models, and fuel consumption forecasting tools.
</li><li>Ensure all models are validated against nuclear industry standards, regulatory requirements, and plant-specific constraints.
</li><li>Lead the adoption of MLOps best practices for continuous monitoring, retraining, and governance of models deployed in nuclear environments.
</li><li>Drive the adoption of automation, CI/CD pipelines, and advanced monitoring for analytics operations.
</li><li>Lead technical reviews, audits, and assurance activities to maintain high standards of quality, reliability, and compliance.
</li><li>Ensure robust documentation, explainability, and auditability of all models and analytics solutions</li></ul>
</div></div><div><div><h2 class="jobSectionHeader"><b>Professional Certifications</b></h2>
</div><div><p>Relevant certifications in AI/ML, MLOps, and Data Governance.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Qualifications</b></h2>
</div><div><p>Min - Master&rsquo;s degree in data science, computer science, engineering, or related discipline. Proven experience leading data science teams in regulated environments</p>
<p>Pref - PhD or equivalent. Experience in nuclear, energy, or highly regulated sectors.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Experience</b></h2>
</div><div><p>8 years of relevent experience</p></div></div></div></div></div></div></div></div><p></p>

Infomineo

<div>
 <p>
  <strong>
   About us
  </strong>
 </p>
 <p>
  Infomineo is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence. We&rsquo;ve evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise. We offer 3 services to our global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights and Resource Scaling. This is made possible by relying on 3 pillars of excellence:
 </p>
 <p>
  <br/>
 </p>
 <ol>
  <li>
   350+ industry experts spread across 5 offices (Cairo, Casablanca, Mexico City, Dubai, Barcelona).
  </li>
  <li>
   Our proprietary AI orchestrator.
  </li>
  <li>
   Extensive knowledge assets combining 500,000+ delivered case studies and database subscriptions.
  </li>
 </ol>
 <p>
  <br/>
 </p>
 <p>
  Ready to kick start your career with us?
 </p>
 <p>
  <strong>
   Why Infomineo? Here&rsquo;s what sets us apart:
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Shape the Future of Business Insights:
   </strong>
   You will be at the forefront, leading the design and implementation of AI-driven solutions that automate tasks and drive efficiency across our entire service spectrum (Business Research, Content, Design, and Data Analytics).
  </li>
  <li>
   <strong>
    Work with Global Leaders:
   </strong>
   Our clients are industry leaders &mdash; Fortune 500s, top consultancies, governments, and NGOs. You will take ownership of delivering technical solutions that directly support their success.
  </li>
  <li>
   <strong>
    Lead in AI &amp; Technology:
   </strong>
   We foster continuous learning and technical excellence. You will stay ahead of the latest advancements in AI and software engineering, and actively drive innovation across the team.
  </li>
  <li>
   <strong>
    Thrive in a Collaborative Culture:
   </strong>
   We value intellectual curiosity, leadership, and a can-do attitude. You will be encouraged to mentor others, contribute strategic ideas, and make a lasting impact on the company&rsquo;s growth.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About this role:
  </strong>
 </p>
 <p>
  We are seeking an experienced and technically strong individual to join us as
  <strong>
   Senior AI Software Engineer.
  </strong>
  In this role, you will take ownership of designing, developing, and deploying AI-powered data products and analytical applications that serve our internal teams and global clients. You will lead data science and AI initiatives, define best practices for applied AI and analytical solution development, and collaborate closely with engineering, product, and business stakeholders. While the role is primarily data science and AI-focused, you will also leverage your full-stack development background to build production-ready applications, integrate AI capabilities, and support cloud-based deployment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities:
  </strong>
 </p>
 <p>
  <strong>
   Data Science, AI &amp; Applied R&amp;D:
  </strong>
 </p>
 <ul>
  <li>
   Lead the design and development of AI-powered analytical solutions, data products, and intelligent applications that solve complex business problems.
  </li>
  <li>
   Translate business and client requirements into data science approaches, AI workflows, and scalable technical solutions.
  </li>
  <li>
   Design, prototype, and productionize machine learning, LLM, and generative AI solutions with a focus on business value, reliability, and usability.
  </li>
  <li>
   Own the architecture of Retrieval-Augmented Generation (RAG) pipelines, including document processing, vectorization, semantic search, evaluation, and query optimization for enterprise use cases.
  </li>
  <li>
   Design and implement complex AI-powered features by integrating LLM APIs and services using frameworks such as LangChain or equivalent, with a focus on reliability, accuracy, and performance in production.
  </li>
  <li>
   Design, implement, and maintain Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and data sources, enabling context-aware and extensible AI solutions.
  </li>
  <li>
   Develop evaluation frameworks, monitoring approaches, and observability practices for LLM-powered systems to ensure quality, transparency, and continuous improvement.
  </li>
  <li>
   Apply advanced prompt engineering, embedding strategies, and vector database management techniques to improve the performance of AI solutions.
  </li>
  <li>
   Integrate AI outputs into analytical workflows, dashboards, reporting tools, and client delivery pipelines.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Full-Stack Application Development:
  </strong>
 </p>
 <ul>
  <li>
   Design and contribute to the development of production-grade AI and data applications, primarily using Python and backend frameworks such as FastAPI.
  </li>
  <li>
   Build or support frontend interfaces using modern frameworks such as React, Next.js, or Vue to make AI and data products accessible to business users and clients.
  </li>
  <li>
   Collaborate with software engineers to define scalable application architectures, API standards, and integration patterns.
  </li>
  <li>
   Develop and maintain REST API integrations with third-party AI services, enterprise SaaS platforms, internal tools, and external data sources.
  </li>
  <li>
   Ensure that data science prototypes are translated into maintainable, secure, and scalable production solutions.
  </li>
  <li>
   Participate in code reviews, define technical best practices, and contribute to a high-quality engineering and data science culture.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Cloud, Deployment &amp; MLOps:
  </strong>
 </p>
 <ul>
  <li>
   Support the containerization and cloud deployment of AI and data applications, preferably on Google Cloud Platform using GKE and Artifact Registry, while remaining adaptable to other cloud environments.
  </li>
  <li>
   Design and maintain CI/CD pipelines using GitHub Actions or equivalent tools to ensure reliable and repeatable releases.
  </li>
  <li>
   Apply MLOps and LLMOps practices to manage experimentation, deployment, monitoring, and continuous improvement of AI systems.
  </li>
  <li>
   Collaborate with engineering and infrastructure teams to ensure the reliability, scalability, and performance of production environments.
  </li>
  <li>
   Proactively identify performance bottlenecks in AI workflows, data pipelines, application layers, and infrastructure.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Technical Leadership &amp; Collaboration:
  </strong>
 </p>
 <ul>
  <li>
   Lead applied AI and data science initiatives from discovery and prototyping through production deployment.
  </li>
  <li>
   Mentor junior data scientists, AI engineers, and developers on data science methods, AI integration, coding practices, and production readiness.
  </li>
  <li>
   Work closely with product teams, consultants, analysts, and non-technical stakeholders to ensure solutions are aligned with business needs.
  </li>
  <li>
   Define standards and best practices for AI solution design, evaluation, documentation, and delivery.
  </li>
  <li>
   Communicate complex technical concepts clearly to both technical and non-technical audiences.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications:
  </strong>
 </p>
 <ul>
  <li>
   4 to 6 years of experience in data science, AI development, applied machine learning, or related technical roles, with hands-on experience delivering production-grade AI or data products.
  </li>
  <li>
   Strong proficiency in Python, with experience using data science, machine learning, and AI libraries and frameworks.
  </li>
  <li>
   Solid full-stack development background, including experience with backend frameworks such as FastAPI and modern frontend frameworks such as React, Next.js, or Vue.
  </li>
  <li>
   Deep understanding of LLMs, RAG architectures, generative AI workflows, and production-grade AI service integration, including tools such as OpenAI, Gemini, LangChain, or equivalent.
  </li>
  <li>
   Proven experience designing and implementing Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and enterprise data sources.
  </li>
  <li>
   Experience building analytical workflows, dashboards, data pipelines, or AI-powered decision-support tools in a client delivery or enterprise context.
  </li>
  <li>
   Hands-on experience with Docker and cloud deployment on at least one major cloud platform such as GCP, AWS, Azure, or equivalent.
  </li>
  <li>
   Familiarity with container orchestration, artifact management, CI/CD pipelines, GitHub Actions, GitOps workflows, and branching strategies.
  </li>
  <li>
   Strong understanding of LLM observability, AI evaluation, performance monitoring, and production reliability practices.
  </li>
  <li>
   Demonstrated ability to lead technical initiatives, mentor junior team members, and collaborate effectively with product teams and business stakeholders.
  </li>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Software Engineering, Statistics, Applied Mathematics, or a related field.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred Skills:
  </strong>
 </p>
 <ul>
  <li>
   Experience with agentic AI frameworks such as LangGraph or similar orchestration tools for building multi-step AI workflows.
  </li>
  <li>
   Knowledge of advanced prompt engineering, vector database management, embedding model optimization, and AI evaluation techniques.
  </li>
  <li>
   Experience with MLOps or LLMOps practices, including experiment tracking, model monitoring, and AI quality evaluation.
  </li>
  <li>
   Experience with Infrastructure as Code tools such as Terraform or Pulumi.
  </li>
  <li>
   Experience designing data models, analytical pipelines, or BI/dashboard solutions.
  </li>
  <li>
   Relevant certifications such as Google Cloud Professional Data Engineer, Google Cloud Professional Machine Learning Engineer, Google Cloud Professional Developer, or similar cloud and AI credentials.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What we offer:
  </strong>
 </p>
 <ul>
  <li>
   A competitive compensation and benefits package.
  </li>
  <li>
   The opportunity to lead AI and technology initiatives with real global impact.
  </li>
  <li>
   A dynamic and supportive work environment that values leadership, innovation, and your contributions.
  </li>
  <li>
   Continuous learning and professional development opportunities to propel your career forward in AI and software engineering.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Application Process:
  </strong>
 </p>
 <p>
  Candidates are invited to submit a resume, cover letter, and any relevant portfolio or GitHub links showcasing their experience in web application development, AI integration, and cloud deployment. Shortlisted candidates will undergo a technical assessment and interview to demonstrate their skills and technical leadership capabilities.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Infomineo: Where brilliant minds meet to shape the future of business.
  </strong>
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AI & Analytics - Sr. Software Engineer with AI Background - Cairo

Vibrant Emotional Health

<div><p><b>Department: Technology
</b><br>
<b>Reports to: Chief Technology Officer
</b><br>
<b>Travel: ~10%
</b></p><p><b>Salary Range: $180,000 - $200,000
</b></p><p></p><p><b>Vibrant Emotional Health&rsquo;s groundbreaking solutions have delivered high quality services and support, when, where and how people need it for over 50 years. Through our state-of-the-art technology-enabled services, community wellness programs, and advocacy and education work, we are building a society in which emotional wellness can be a reality for everyone.
</b></p><p></p><p><b>Position Overview:
</b></p><p></p><p>The Assistant Vice President, Data is a senior enterprise data leadership role within Vibrant's Data Pillar, responsible for unifying and leading Vibrant's full data capability - spanning analytics and reporting, data science, machine learning, and AI. Reporting directly to the Chief Technology Officer, this leader serves as the single accountable executive for Vibrant's entire data function during an intentional consolidation phase designed to build integrated data maturity before the function expands into two distinct leadership tracks.
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In this role, the AVP, Data ensures that Vibrant's analytics infrastructure, machine learning programs, AI adoption, and data governance operate as a coherent ecosystem. The AVP partners with program leadership and staff as well as Vibrant's executive team to deliver data products, predictive models, and responsible AI capabilities that directly improve outcomes for people in crisis.</p>
<p></p><p><b>Duties/Responsibilities:
</b></p><ul><li>Define and lead an integrated data strategy spanning analytics &amp; reporting, data science, machine learning, and AI - aligned to Vibrant's goals and program priorities. Serve as Vibrant's senior data executive: advising the CTO, executive leadership, and the Board on data capabilities, AI adoption, and investment priorities.</li>
<li>Build and manage the departmental roadmap, establishing the organizational architecture and roal definitions. Lead Vibrant's data governance council responsibilities, including oversight of data standards, KPI frameworks, and program data sharing requirements.</li>
<li>Own budget planning, tracking, and forecasting for the Data function, ensuring spend aligns with approved FY budgets, funding stream requirements, and grant compliance obligations</li>
<li>Manage the AI use approval pipeline with internal and external leadershipo: preparing documentation, use case justifications, and responsible AI assessments for all AI/ML deployments under the cooperative agreement.</li>
<li>Lead the strategy, architecture, and delivery of Vibrant's enterprise analytics and reporting platform, supporting operational, compliance, and strategic reporting needs across programs and corporate functions.</li>
<li>Ensure delivery of program-required reporting, including automated dashboards for network operational and quality metrics, crisis contact center performance reporting, and federally mandated data submissions.</li>
<li>Design and deliver executive dashboards and performance scorecards for Vibrant's leadership team, Board of Directors, and crisis center network.</li>
<li>Own the data governance framework for reporting outputs: data definitions, lineage documentation, and quality assurance protocols.</li>
<li>Evaluate and implement BI and analytics tooling (e.g., Tableau, Power BI, Looker) to modernize Vibrant's reporting infrastructure.</li>
<li>Lead Vibrant's response to audit and compliance data requests, including federal OIG reviews and GAO inquiries.</li>
<li>Champion data accessibility and health equity analytics across Vibrant's programs, ensuring disaggregated reporting by race, ethnicity, geography, and other equity dimensions.</li>
<li>Oversee development and deployment of machine learning models across use cases including crisis risk stratification, call routing optimization, quality assurance automation, NLP-driven conversation analytics, and population health analytics.</li>
<li>Establish responsible AI governance frameworks, including bias auditing, model explainability, and ethical review protocols appropriate for behavioral health contexts and required by the program.</li>
<li>Partner with the peers to advance the research agenda, maintain scientific standards, and translate research findings into production-ready models.</li>
<li>Evaluate and integrate emerging AI technologies - including large language models and generative AI - with appropriate rigor, human-in-the-loop safeguards, and program approvals for mission-critical applications.</li>
<li>Ensure all AI/ML systems meet regulatory requirements.</li>
<li>Build, develop, and retain a high-performing data organization spanning Analytics &amp; Reporting, Data Science, ML Engineering, MLOps, AI Ethics, Data Quality, and Data Governance functions.</li>
<li>Manage and mentor direct reportsManage the analytics and data science product roadmap in partnership with internal teams, ensuring data investments are sequenced against program stakeholder needs and regulatory requirements.</li>
<li>Represent Vibrant's data and AI capabilities in external partner engagements, grant applications, and public health research contexts.</li>
<li>Other duties as assigned.</li>
</ul><p></p><p><b>Required Skills/Abilities:
</b></p><ul><li>Executive-level experience defining and executing integrated data strategies spanning analytics, business intelligence, data science, and AI within complex, mission-driven organizations.
</li><li>Deep expertise in enterprise analytics, BI platform architecture, and modern data stack technologies (e.g., dbt , Snowflake, Tableau/Power BI/Looker).
</li><li>Strong command of data science and machine learning: proficiency in Python-based ML ecosystems (scikit-learn, PyTorch, Hugging Face), end-to-end model lifecycle management, NLP, and responsible AI.
</li><li>Proven ability to build, scale, and lead high-performing multidisciplinary data teams across analytics, data science, and ML engineering functions.
</li><li>Demonstrated experience establishing responsible AI frameworks - bias detection, model explainability, and ethical review - in high-stakes, human-centered environments.
</li><li>Strong understanding of HIPAA, 42 CFR Part 2, federal data governance requirements, and AI compliance in health and human services contexts.
</li><li>Ability to translate complex data and AI concepts into clear, actionable insights for executive leadership, Board members, federal partners, and non-technical stakeholders.
</li><li>Experience partnering cross-functionally with Product, Engineering, Legal, and Compliance teams to govern and deploy data and AI capabilities responsibly.
</li><li>Demonstrated commitment to advancing health equity analytics, inclusive data practices, and mission-aligned AI adoption.
</li></ul><p></p><p><b>Required Qualifications:
</b></p><ul><li>12+ years of progressive experience in analytics, data science, or data leadership roles, with at least 5 years in a senior leadership capacity with direct accountability for both analytics and data science or ML functions.
</li><li>Bachelor's degree in a quantitative field required; Master's degree or higher preferred (Computer Science, Statistics, Data Science, Public Health, or related field).
</li><li>Demonstrated experience leading programs, teams, or operational units across multiple data disciplines, with accountability for project execution, team performance, and cross-functional delivery.
</li><li>Deep expertise in BI platforms (Tableau, Power BI, Looker, or equivalent), modern data stack technologies (dbt, Snowflake, BigQuery), and ML/AI frameworks (PyTorch, scikit-learn, Hugging Face, or equivalent).
</li><li>Proven track record building enterprise data infrastructure and applied AI/ML programs in complex, regulated environments.
</li><li>Experience in mission-driven, nonprofit, healthcare, government, or other highly regulated environments, with familiarity in compliance-driven reporting and data governance frameworks preferred.
</li><li>Experience with SAMHSA-funded programs, federal cooperative agreements, or similarly regulated grant environments strongly preferred.
</li></ul><p></p><p><b>Physical Requirements:
</b></p><ul><li>Must be able to remain in a stationary position at least 50% of the time</li>
<li>Will constantly operate a computer and other office productivity machinery, such as a calculator, copy machine, and computer printer</li>
<li>Will frequently communicate over video calls with internal and external stakeholders</li></ul><br>
<p>We determine base pay through a comprehensive review of skills, experience, education, certifications, geographic location, and other relevant factors. The range listed reflects the compensation parameters for the role and does not represent the full compensation package. A complete overview of compensation and benefits will be provided by the Talent Acquisition team during the hiring process.
</p><p></p><p>Full time employees will be eligible for excellent comprehensive benefits, including medical, dental, vision, supplemental income insurance, employer paid disability insurance, employer paid life insurance, pre-tax FSA for medical and dependent care, and 401K available.
</p><p></p><p>Studies have shown that women and people of color are less likely to apply for jobs unless they believe they are able to perform every task in the job description. We are most interested in finding the best candidate for the job, and that candidate may be one who comes from a less traditional background. Vibrant will consider any equivalent combination of knowledge, skills, education and experience to meet minimum qualifications. If you are interested in applying, we encourage you to think broadly about your background and skill set for the role.
</p><p></p><p>Vibrant Emotional Health is an equal opportunity employer. Applicants are considered for positions without regard to veteran status, uniformed service member status, race, creed, color, religion, gender, gender identity, sex, sexual orientation, citizenship status, national origin, marital status, age, physical or mental disability, genetic information, caregiver status or any other category protected by applicable federal, state or local laws.
</p><p></p><p>Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Vibrant does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted on our careers page and all communications from the Vibrant recruiting team and/or hiring managers will be from an @vibrant.org email address.</p></div><p></p>

Assistant Vice President, Data

Baylor College of Medicine

<div><div><div><div><h2 class="jobSectionHeader"><b>Summary</b></h2></div><div><p>
The Michael E. DeBakey Department of Surgery at the Baylor College of Medicine (BCM) seeks a highly qualified individual with a PhD and postdoctoral experience in Computer Science, Data Science, Medical Informatics or Equivalent Field. The Assistant Professor &ndash; Data Scientist would serve as scientific lead with Dr. Ravi Ghanta, overseeing the Department of Surgery ATLAS AI program to develop innovative AI applications in surgery and healthcare. The work spans AI applications in healthcare including machine vision, robotics, image analysis, natural language processing, and predictive modeling.</p><p></p><p><br>
Under this role, the Assistant Professor will work with a team of post-doctoral computer scientists and engineers on NIH-funded research projects. The Assistant Professor is expected to oversee data engineering of electronic health data for machine learning applications, interoperability with electronic health record (EHR) systems, and evaluation of algorithm predictive performance. The Assistant Professor will interact directly with postdoctoral fellows, graduate students, and medical students.</p></div></div><div><div><h2 class="jobSectionHeader"><b>
Job Duties</b></h2></div><div><ul><li>
Oversee and coordinate logistics and execution of various research projects.</li><li>
Manage project progress and execution of project goals and milestones.</li><li>
Plan and direct research experiments.</li><li>
Organize, evaluate, and analyze data with other researchers.</li><li>
Develop research techniques and perform applications required for specific research projects.</li><li>
Conduct literature searches and summarize information in an appropriate format for a particular study.</li><li>
Document results of experiments and reports to principal investigators.</li><li>
Supervise, schedule and coordinate the activities of the research team involved in multiple research projects.</li><li>
Write progress reports, manuscripts and grant proposals.</li><li>
Lead clinical studies and participate in research involving human subjects. Interact directly with clinicians, surgeons, and pathologists to fulfill the aims of the research projects.</li><li>
Supervise research staff including graduate and undergraduate students.</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
Minimum Qualifications</b></h2></div><div><ul><li>
Ph.D. in computer science, data science, medical informatics, or related field.</li><li>
Successful track record of collaboration with clinical investigators and in interdisciplinary teams; accomplished academic record sufficient to fulfill criteria for an assistant professor level faculty appointment at Baylor College of Medicine.</li></ul></div></div></div><p></p><p><br>
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.</p></div><p></p>

Assistant Professor - Artificial Intelligence and Data Scientist

Three Dimension Physical Performance

<div><div><b>Job Summary:</b></div><div>
We are currently hiring a highly skilled and experienced Sport Scientist &amp; Data Analyst to join our dynamic team at 3Dimensions. If you're passionate about optimizing athletic performance through science and data, we want to hear from you!<br>
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<b>Key Responsibilities:</b></div><ul><li>
He will oversee and optimize fitness programs and lead the integration of scientific principles into training protocols.</li><li>
Supervise a team of trainers and provide strategic insights to enhance overall fitness outcomes.</li></ul><div><br>
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Requirements:</b></div><ul><li><b>
Education: </b>Bachelor's in Sports Science, Exercise Physiology, or a related field. MSC preferred.</li><li><b>
Certification: </b>Certified as a sport scientist and trainer in the candidate's home country, with additional certifications in data analysis preferred.</li><li>
Minimum 2-4 years of experience in a fitness or sports training environment, with significant experience in a senior or supervisory role.</li></ul></div><div></div>

Sports Scientist and Data Analyst

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