machine learning scientist

New York University Abu Dhabi

<div>
 The Center for Technology, Economics, and Development (CTED) at New York University Abu Dhabi (NYUAD) invites applications from individuals to be appointed as a Junior Research Scientist (AI-Blockchain Project) for a one-year period, with the possibility of renewal conditional on excellent performance.
 <br/>
 <br/>
 The Junior Research Scientist (AI-Blockchain Research) will support advanced, quantitatively intensive research at CTED with a primary focus on artificial intelligence, machine learning, mathematical modeling, and computational analysis. The Junior Research Scientist will play a central role in supporting research design, algorithmic development, data analysis, and coding tasks across CTED&rsquo;s interdisciplinary projects. Working under the direction of the Principal Investigator (PI), Dr. Yaw Nyarko, and Co-Principal Investigator (Co-PI), Dr. Ra&scaron;a Karapand&zcaron;a, the Junior Research Scientist will contribute to AI-driven and blockchain-enabled research related to commodities markets and economic development. The role requires strong foundations in mathematics and computer science, including statistical learning, optimization, simulation, and algorithmic reasoning. The successful candidate will use programming and computational tools (including Python, MATLAB, and related libraries) to develop, test, and evaluate machine learning models; review, proofread, and execute formal mathematical proofs; implement optimization and simulation-based methods; and analyze large and complex datasets. Responsibilities include supporting experimental and field-based research, preparing literature reviews, translating complex AI and mathematical findings into clear written outputs, and contributing to research reports, concept notes, and academic publications.
 <br/>
 <br/>
 Candidates must hold a Master&rsquo;s degree in Computer Science, Data Science, Mathematics or a related field (e.g., Economics with a strong mathematics background). and have less than five years of relevant research experience; or hold a Bachelor&rsquo;s degree in a relevant field with any level of research experience. Applicants must have extensive coding experience, and preferably, applicants will have experience conducting field research in emerging countries and working on randomized controlled trials (RCTs). Applicants with experience working in programming languages such as Python, JavaScript, and/or MATLAB, a strong interest in economic and quantitative research and the willingness to learn about the blockchain, are encouraged to apply. Experience in web development, blockchain, commodities markets, and technology and economic development will be considered a plus. The successful candidate will work in a multidisciplinary environment, working autonomously, but as a team member under the direction of the Principal Investigator.
 <br/>
 <br/>
 The terms of employment are very competitive. Applications will be accepted immediately, and candidates will be considered until the position is filled. For consideration, applicants need to submit a cover letter, curriculum vitae/resume, transcript of degree, and one academic writing sample, and 2 contact references, all in PDF format. If you have any questions, please email amp330@nyu.edu.
 <br/>
 <br/>
 NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community.
 <br/>
 <br/>
 Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply.
 <br/>
 <br/>
 <strong>
  About NYU Abu Dhabi
  <br/>
  <br/>
 </strong>
 https://nyuad.nyu.edu/en/
 <br/>
 <br/>
 NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity&rsquo;s shared challenges. NYU Abu Dhabi&rsquo;s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.
 <br/>
 <br/>
 NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.
 <br/>
 <br/>
 Students are drawn from among the world&rsquo;s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed.
 <br/>
 <br/>
 Working for NYUAD
 <br/>
 <br/>
 At NYUAD, we recognize that Abu Dhabi is more than where you work; it&rsquo;s your home. In order for faculty/academic staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to faculty/academic staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority. Visit our website for more information on benefits for you and your dependents.
 <br/>
 <br/>
 Join NYU Abu Dhabi, an exceptional place for exceptional people.
 <br/>
 <br/>
 NYUAD values belonging and respect; such principles are fundamental to the university&rsquo;s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University&rsquo;s mission.
 <br/>
 <br/>
 <strong>
  Equal Employment Opportunity Statement
  <br/>
  <br/>
 </strong>
 <strong>
  For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
  <br/>
  <br/>
 </strong>
 NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.
 <br/>
 <br/>
 <strong>
  Sustainability Statement
  <br/>
  <br/>
 </strong>
 NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability
</div>


Junior Research Scientist in the Division of Social Science (CTED) - Dr. Yaw Nyarko

TMC Middle East

<div>
 <p>
  TMC Middle East is currently engaged in a project with one of our prestigious customers in UAE.
 </p>
 <p>
  We are seeking a highly capable Senior Data Scientist expert to help TMC to deliver this assignment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the Role:
  </strong>
 </p>
 <p>
  Position: Senior Data Scientist
 </p>
 <p>
  Location: Abu Dhabi
 </p>
 <p>
  Experience: 8+ Years
 </p>
 <p>
  Preferred: Western &amp; Diverse candidates
 </p>
 <p>
  <br/>
 </p>
 <p>
  Technical Requirements
 </p>
 <p>
  ● Core AI/ML: Expert proficiency in Python and standard ML libraries (TensorFlow/PyTorch,
 </p>
 <p>
  Scikit-learn, Pandas, NumPy). Strong grasp of both supervised and unsupervised learning
 </p>
 <p>
  techniques.
 </p>
 <p>
  ● NLP &amp; LLMs: Deep experience with transformer-based models (GPT, BERT, Llama) and
 </p>
 <p>
  prompt engineering techniques (few-shot learning, fine-tuning) for domain-specific tasks.
 </p>
 <p>
  ● Data Engineering: Proficiency in handling complex data structures (JSON, XML) and
 </p>
 <p>
  familiarity with database querying (SQL/NoSQL) or graph data structures. Experience with
 </p>
 <p>
  data extraction from specialized formats is a significant plus.
 </p>
 <p>
  ● Backend Awareness: Understanding of how to expose models via RESTful APIs
 </p>
 <p>
  (Flask/FastAPI) and integrate them into larger software architectures.
 </p>
 <p>
  ● Statistics: Solid understanding of statistics, probability distribution, A/B testing. Adept at
 </p>
 <p>
  identifying and mitigating biases in datasets.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Professional Qualifications
 </p>
 <p>
  ● Experience: 5+ years of experience in Data Science or Machine Learning, with a proven
 </p>
 <p>
  track record of deploying models into production environments.
 </p>
 <p>
  ● Domain Adaptability: Ability to quickly grasp complex domain terminology (e.g.,
 </p>
 <p>
  construction regulations, defense standards, supply chain taxonomies) and translate them
 </p>
 <p>
  into logic.
 </p>
 <p>
  ● Structured Delivery: Experience working in structured delivery models
 </p>
 <p>
  (Agile/Sprint-based) while adhering to rigorous validation and verification standards.
 </p>
 <p>
  ● Collaboration: Strong communication skills to work effectively with Domain Experts,
 </p>
 <p>
  Backend Engineers, and Product Managers to align model outputs with real-world
 </p>
 <p>
  business logic.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Please share your CV with the title of
  <strong>
   Senior Data Scientist
  </strong>
 </p>
 <p>
  Mail ID : vigneshwari.sivalingam@tmc-employeneurs.com
 </p>
</div>


Senior Data Scientist

Arab Monetary Fund

<div>
 <p>
  <strong>
   Job Purpose:
  </strong>
 </p>
 <p>
  The Data Scientist supports the design and implementation of advanced data analytics solutions to enhance AMF&rsquo;s research, policy analysis, and decision-making capabilities. The role focuses on applying machine learning, AI, and statistical modelling to unlock insights, strengthen data integration, and advance innovation within the organization.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Roles and Responsibilities
 </p>
 <p>
  Key Accountabilities
 </p>
 <ul>
  <li>
   Design and implement statistical models, machine learning algorithms, and AI tools for large-scale structured and unstructured data
  </li>
  <li>
   Conduct predictive and prescriptive analytics to support economic and financial policy initiatives
  </li>
  <li>
   Continuously enhance models for performance, accuracy, and scalability
  </li>
  <li>
   Clean, transform, and manage diverse data sources using automated ETL pipelines
  </li>
  <li>
   Collaborate with IT to optimize data infrastructure for secure and efficient access
  </li>
  <li>
   Ensure data quality and alignment with organizational data architecture standards
  </li>
  <li>
   Partner with research teams on data-driven approaches for frontier topics (e.g., digital economy, AI, climate, financial innovation)
  </li>
  <li>
   Apply advanced techniques such as deep learning and NLP to enhance research
  </li>
  <li>
   Monitor developments in data science and introduce relevant tools and techniques
  </li>
  <li>
   Develop dashboards and visualizations to communicate insights to policymakers
  </li>
  <li>
   Create data storytelling outputs for publications, policy discussions, and training
  </li>
  <li>
   Ensure consistent and accessible data presentation across platforms and reports
  </li>
  <li>
   Comply with data protection regulations, internal policies, and ethical AI standards
  </li>
  <li>
   Support implementation of data governance frameworks and quality standards
  </li>
  <li>
   Participate in audits and compliance reviews related to data use and access
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Qualifications and Requirements:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Knowledge and Experience:
  </strong>
 </p>
 <ul>
  <li>
   Minimum 5 years of experience in:
  </li>
  <li>
   Data science
  </li>
  <li>
   Machine learning
  </li>
  <li>
   Advanced analytics
  </li>
  <li>
   Preferably within economic, financial, or public policy sectors
  </li>
  <li>
   Proven ability to develop predictive models and deliver actionable insights
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Education:
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree in:
  </li>
  <li>
   Data science
  </li>
  <li>
   Computer science
  </li>
  <li>
   Statistics
  </li>
  <li>
   Economics Or a related field
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Certifications (Preferred):
  </strong>
 </p>
 <ul>
  <li>
   Recognized certifications such as:
  </li>
  <li>
   Google Data Analytics
  </li>
  <li>
   IBM Data Science
  </li>
  <li>
   SAS
  </li>
  <li>
   CAP (Certified Analytics Professional)
  </li>
 </ul>
 <p>
  <br/>
 </p>
</div>


Data Scientist

Masdar

<div><b>Company Description</b><p><br>
Established in 2006, Masdar (Abu Dhabi Future Energy Company) is a global clean energy leader, transforming how the world produces and consumes energy through bold innovation and commercial excellence.</p><p>
Masdar is a clean energy investor, developer and operator, advancing renewable energy projects across key markets and technologies, with a global project portfolio capacity to date of over <b>65</b> gigawatts (GW).</p><p>
Jointly owned by <b>TAQA, ADNOC and Mubadala</b>, Masdar is driving the scale-up of renewables worldwide, targeting a portfolio capacity of 100GW by 2030.</p><b><br>
Job Description</b><p><br>
To support the development of analytics, AI, and data products while building foundational capabilities, as part of Masdar&rsquo;s national-talent development within the AI Products &amp; Analytics Technology CoE.</p><p><b>
Key Accountabilities</b> :</p><ul><li>
Perform data preparation, cleaning, and analysis.</li><li>
Support the development of analytical models and data pipelines across key use cases</li><li>
Assist in implementing machine learning, statistical, and optimization models under guidance from senior team members</li><li>
Perform data cleaning, preprocessing, and exploratory data analysis (EDA)</li><li>
Translate analytical outputs into clear insights, visualizations, and reports</li><li>
Support the delivery of data-driven recommendations to inform operational and strategic decisions</li><li>
Contribute to dashboards and tools that enhance visibility into performance and forecasts</li><li>
Develop dashboards and reports on the CoE&rsquo;s BI platforms.</li><li>
Support AI model development, testing, and documentation.</li><li>
Work closely with the Senior Decision Scientist to Build and refine models, Validate results and ensure quality outputs, and Understand business context and decision frameworks</li><li>
Participate in code reviews, model reviews, and knowledge-sharing sessions</li><li>
Ensure high standards of data integrity, quality checks, and documentation</li><li>
Work with structured and unstructured datasets from multiple sources</li><li>
Support the maintenance of reproducible and well-documented codebases</li><li>
Build foundational skills in data science, AI, and platform tools through structured development.</li><li>
Apply best practices in coding, modeling, and analytics inspired by industry-leading organizations</li><li>
Engage with stakeholders across operations, digital, and strategy teams to understand data needs</li><li>
Support the translation of business questions into analytical tasks</li><li>
Communicate findings in a clear and structured manner appropriate for different audiences</li></ul><br>
<b>
Qualifications</b><p><b><br>
Preferred Qualifications:</b></p><ul><li>
Bachelor&rsquo;s degree in Computer Science, Data Science, Engineering, or a related field; UAE National (National Talent programme). Strong foundation in statistics, linear algebra, and data analysis.<b>
</b></li></ul><p><b>Preferred Experience:</b></p><ul><li>
1&ndash;3 years of experience in data science, analytics, or related fields (internships included)</li><li>
Job-Exposure to energy, utilities, or financial analytics is advantageous but not mandatory</li><li>
Demonstrated experience working on data-driven projects (academic or professional)</li></ul><p><b>
Technical Skills:</b></p><ul><li>
Proficiency in Python, SQL, or similar programming languages</li><li>
Familiarity with:</li><li>
Data analysis libraries (e.g., Pandas, NumPy)</li><li>
Visualization tools (e.g., Power BI, Tableau, Matplotlib)</li><li>
Basic machine learning concepts and frameworks</li><li>
Understanding of data pipelines and data wrangling techniques</li><li>
Exposure to cloud platforms or big-data tools is a plus</li></ul><p><b>
Behavioral Competencies:</b></p><ul><li>
Strong analytical thinking and problem-solving skills</li><li>
Curiosity and eagerness to learn and grow in a fast-paced environment</li><li>
Ability to take direction, absorb feedback, and continuously improve</li><li>
Good communication skills with the ability to explain findings clearly</li><li>
Collaborative mindset and strong attention to detail</li></ul><p></p><p><br>
Role is to be based in <b>Abu Dhabi, UAE.</b></p><b><br>
Additional Information</b><div></div><p><br>
As part of the application process, we will collect, store and process personal information about you.</p><p>
Masdar will use your personal information in accordance with our <b>Candidate Privacy Notice</b>, which provides details on the purposes for which your data is processed.</p></div>

Associate Data / Decision Scientist (UAEN)

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: 3823
</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>We are seeking a versatile and experienced Data Engineer to join our team. The ideal candidate will have a strong background in data engineering and machine learning, with the ability to design, build, and maintain data pipelines, as well as develop and deploy machine learning models. This role requires a deep understanding of data lakehouses, such as Databricks and Azure Fabric, and the ability to work collaboratively with cross-functional teams to deliver data-driven solutions.<br>
<br>
</p></div></div><div><div><h2 class="jobSectionHeader"><b>Key Activities, Responsibility &amp; Accountability</b></h2>
</div><div><div>Key Responsibilities:
<br>
Data Engineering:
<br>
<ul><li>Design, build, and maintain scalable data pipelines and ETL processes.
</li><li>Work with large datasets and data lakehouses, including Databricks and Azure Fabric.
</li><li>Ensure data quality, integrity, and security across all data pipelines.
</li><li>Optimize data storage and retrieval processes for performance and efficiency.
</li></ul>Machine Learning Engineering:
<br>
<ul><li>Develop, implement, and optimize machine learning models and algorithms.
</li><li>Perform data analysis and model tuning to improve accuracy and performance.
</li><li>Deploy machine learning models into production environments.
</li><li>Monitor and maintain the performance of deployed models.
</li></ul>Collaboration:
<br>
<ul><li>Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
</li><li>Work closely with data scientists, analysts, and other stakeholders to ensure seamless integration of data and models.
</li></ul>Continuous Learning:
<br>
<ul><li>Stay up-to-date with the latest advancements in data engineering and machine learning.
</li><li>Participate in training and development opportunities to enhance skills and knowledge.<br>
</li></ul></div></div></div><div><div><h2 class="jobSectionHeader"><b>Responsibilities &amp; Accountabilities (contd.)</b></h2>
</div></div><div></div><div><div><h2 class="jobSectionHeader"><b>Professional Certifications</b></h2>
</div></div><div></div><div><div><h2 class="jobSectionHeader"><b>Qualifications</b></h2>
</div><div><p>Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Experience</b></h2>
</div><div><ul><li>5-10 years of experience in data engineering and machine learning.
</li><li>Proficiency in programming languages such as Python, R, or SQL.
</li><li>Experience with data lakehouses, particularly Databricks and Azure Fabric.
</li><li>Strong analytical and problem-solving skills.
</li><li>Excellent communication and teamwork abilities.
</li><li>Ability to work independently and manage multiple projects simultaneously.</li></ul></div></div></div></div></div></div></div></div><p></p>

Data Engineer

Contango

<div>
 <strong>
  Contract duration:
 </strong>
 6 months (with a potential extension)
 <br/>
 <br/>
 <strong>
  Engagement Type:
 </strong>
 Full-time
 <br/>
 <br/>
 <strong>
  Start date:
 </strong>
 July 2026
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 Abu Dhabi (on-site)
 <br/>
 <br/>
 <strong>
  About Contango
  <br/>
  <br/>
 </strong>
 Contango is the strategic partner for transformative growth and sustained success for the ADQ portfolio. Our team excels in providing comprehensive growth solutions that combine global best practices with local market expertise. We focus on long-term value creation, empowering our clients to achieve the full scale of their aspirations. As a trusted advisor to ADQ's portfolio companies, Contango helps CEOs drive strategic growth initiatives, navigate disruptive forces, and maximize long-term value creation.
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 As a Senior Data Scientist, you will independently work on specific data projects and be responsible for implementing analytical solutions. You will design, build, deploy, and support end-to-end Data &amp; AI solutions. You will translate complex business challenges into scalable, production-ready analytics and machine learning systems, collaborating closely with product, data engineering, and architecture stakeholders to deliver measurable impact.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Use Case Framing &amp; Solution Design
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Translate client business problems into end-to-end system architectures that combine Data, ML, and software components.
  </li>
  <li>
   Lead the design of scalable, modular AI solutions, defining services, interfaces, and data flows.
  </li>
  <li>
   Make explicit trade-offs across performance, cost, latency, and maintainability.
  </li>
  <li>
   Define success metrics, SLAs, and non-functional requirements (reliability, security, scalability).
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Engineering &amp; Feature Systems
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and implement robust data pipelines (batch and streaming) with strong guarantees on quality, lineage, and observability.
  </li>
  <li>
   Build and manage feature pipelines and feature stores, ensuring consistency between training and inference.
  </li>
  <li>
   Collaborate with platform teams to define data models, schemas, and storage strategies.
  </li>
  <li>
   Enforce standards for data validation, testing, and monitoring within production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Applied ML &amp; Production-Grade Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop ML solutions using production-quality code (Python/JS), following software engineering best practices.
  </li>
  <li>
   Structure codebases into maintainable, testable modules, with clear separation of concerns.
  </li>
  <li>
   Implement unit, integration, and end-to-end tests for data and ML components.
  </li>
  <li>
   Package models and logic into deployable services (APIs, microservices, batch jobs) using modern frameworks.
  </li>
  <li>
   Balance model sophistication with system performance, latency, and operational constraints.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  MLOps, DevOps &amp; Platform Integration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build and maintain CI/CD pipelines for ML systems, including automated testing, validation, and deployment.
  </li>
  <li>
   Containerize and deploy services using Docker, Kubernetes, and cloud-native tooling.
  </li>
  <li>
   Implement model versioning, experiment tracking, and artifact management.
  </li>
  <li>
   Design monitoring and observability systems (logs, metrics, alerts) for both data and model performance.
  </li>
  <li>
   Automate retraining, rollback, and release strategies to ensure system resilience.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  System Reliability, Scalability &amp; Security
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design systems for high availability, fault tolerance, and horizontal scalability.
  </li>
  <li>
   Optimize performance across data pipelines and inference services (latency, throughput, cost).
  </li>
  <li>
   Apply secure coding practices, access controls, and data protection standards.
  </li>
  <li>
   Manage technical debt and ensure long-term maintainability of production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Documentation, Standards &amp; Engineering Excellence
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Produce developer-focused documentation (APIs, architecture diagrams, runbooks).
  </li>
  <li>
   Establish and enforce coding standards, review processes, and engineering best practices.
  </li>
  <li>
   Build reusable libraries, SDKs, and internal frameworks to accelerate delivery.
  </li>
  <li>
   Drive continuous improvement in engineering maturity, tooling, and delivery practices across the consultancy.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Experience And Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Prior experience at management consulting firms and/or Big Tech is an advantage.
  </li>
  <li>
   Client-serving experience is an advantage.
  </li>
  <li>
   5+ years of experience in data science or a related analytical field.
  </li>
  <li>
   5+ years delivering end-to-end analytics/ML solutions from problem framing through deployment and ongoing monitoring in production.
  </li>
  <li>
   Experience applying software engineering methodologies and best practices, including coding standards, code reviews, build processes, testing, and security.
  </li>
  <li>
   Prior experience in developing AI solutions on public cloud services is an advantage.
  </li>
  <li>
   Bachelor&rsquo;s degree (Master&rsquo;s preferred) in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering).
  </li>
  <li>
   Technical Expertise:
  </li>
  <ul>
   <li>
    Coding &amp; data querying: Python (pandas/NumPy) and SQL; writing clean, testable code with Git.
   </li>
   <li>
    Statistics &amp; experimentation: Probability/statistics, hypothesis testing, regression, and A/B testing/experimental design.
   </li>
   <li>
    ML modelling: Feature engineering, model selection, cross-validation, metrics, and hyperparameter tuning (supervised/unsupervised).
   </li>
   <li>
    Data prep &amp; analysis: ETL/EDA, data cleaning, handling missing/outliers, and building insight narratives with visuals.
   </li>
  </ul>
 </ul>
</div>


Senior Data Scientist (6 months contract)

<div><p><b>Contract duration: </b>6 months (with a potential extension)<br>
<b>Engagement Type:</b> Full-time<br>
<b>Start date: </b>July 2026<br>
<b>Location:</b> Abu Dhabi (on-site)</p><p><b><br>
About Contango:</b></p><p>
Contango is the strategic partner for transformative growth and sustained success for the ADQ portfolio. Our team excels in providing comprehensive growth solutions that combine global best practices with local market expertise. We focus on long-term value creation, empowering our clients to achieve the full scale of their aspirations. As a trusted advisor to ADQ's portfolio companies, Contango helps CEOs drive strategic growth initiatives, navigate disruptive forces, and maximize long-term value creation.</p><p></p><p><b>
Role Overview</b></p><p>
As a Senior Data Scientist, you will independently work on specific data projects and be responsible for implementing analytical solutions. You will design, build, deploy, and support end-to-end Data &amp; AI solutions. You will translate complex business challenges into scalable, production-ready analytics and machine learning systems, collaborating closely with product, data engineering, and architecture stakeholders to deliver measurable impact.</p><p><b><br>
Key Responsibilities</b></p><p><b>
Use Case Framing &amp; Solution Design</b></p><ul><li><p>
Translate client business problems into end-to-end system architectures that combine Data, ML, and software components.</p></li><li><p>
Lead the design of scalable, modular AI solutions, defining services, interfaces, and data flows.</p></li><li><p>
Make explicit trade-offs across performance, cost, latency, and maintainability.</p></li><li><p>
Define success metrics, SLAs, and non-functional requirements (reliability, security, scalability).</p></li></ul><p><b>
Data Engineering &amp; Feature Systems</b></p><ul><li><p>
Design and implement robust data pipelines (batch and streaming) with strong guarantees on quality, lineage, and observability.</p></li><li><p>
Build and manage feature pipelines and feature stores, ensuring consistency between training and inference.</p></li><li><p>
Collaborate with platform teams to define data models, schemas, and storage strategies.</p></li><li><p>
Enforce standards for data validation, testing, and monitoring within production systems.</p></li></ul><p><b>
Applied ML &amp; Production-Grade Development</b></p><ul><li><p>
Develop ML solutions using production-quality code (Python/JS), following software engineering best practices.</p></li><li><p>
Structure codebases into maintainable, testable modules, with clear separation of concerns.</p></li><li><p>
Implement unit, integration, and end-to-end tests for data and ML components.</p></li><li><p>
Package models and logic into deployable services (APIs, microservices, batch jobs) using modern frameworks.</p></li><li><p>
Balance model sophistication with system performance, latency, and operational constraints.</p></li></ul><p><b>
MLOps, DevOps &amp; Platform Integration</b></p><ul><li><p>
Build and maintain CI/CD pipelines for ML systems, including automated testing, validation, and deployment.</p></li><li><p>
Containerize and deploy services using Docker, Kubernetes, and cloud-native tooling.</p></li><li><p>
Implement model versioning, experiment tracking, and artifact management.</p></li><li><p>
Design monitoring and observability systems (logs, metrics, alerts) for both data and model performance.</p></li><li><p>
Automate retraining, rollback, and release strategies to ensure system resilience.</p></li></ul><p><b>
System Reliability, Scalability &amp; Security</b></p><ul><li><p>
Design systems for high availability, fault tolerance, and horizontal scalability.</p></li><li><p>
Optimize performance across data pipelines and inference services (latency, throughput, cost).</p></li><li><p>
Apply secure coding practices, access controls, and data protection standards.</p></li><li><p>
Manage technical debt and ensure long-term maintainability of production systems.</p></li></ul><p><b>
Documentation, Standards &amp; Engineering Excellence</b></p><ul><li><p>
Produce developer-focused documentation (APIs, architecture diagrams, runbooks).</p></li><li><p>
Establish and enforce coding standards, review processes, and engineering best practices.</p></li><li><p>
Build reusable libraries, SDKs, and internal frameworks to accelerate delivery.</p></li><li><p>
Drive continuous improvement in engineering maturity, tooling, and delivery practices across the consultancy.</p></li></ul><p></p><p><b>
Required Experience and Qualifications</b></p><ul><li><p>
Prior experience at management consulting firms and/or Big Tech is an advantage.</p></li><li><p>
Client-serving experience is an advantage.</p></li><li><p>
5+ years of experience in data science or a related analytical field.</p></li><li><p>
5+ years delivering end-to-end analytics/ML solutions from problem framing through deployment and ongoing monitoring in production.</p></li><li><p>
Experience applying software engineering methodologies and best practices, including coding standards, code reviews, build processes, testing, and security.</p></li><li><p>
Prior experience in developing AI solutions on public cloud services is an advantage.</p></li><li><p>
Bachelor&rsquo;s degree (Master&rsquo;s preferred) in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering).</p></li><li><p><b>
Technical Expertise:</b></p><ul><li><p>
Coding &amp; data querying: Python (pandas/NumPy) and SQL; writing clean, testable code with Git.</p></li><li><p>
Statistics &amp; experimentation: Probability/statistics, hypothesis testing, regression, and A/B testing/experimental design.</p></li><li><p>
ML modelling: Feature engineering, model selection, cross-validation, metrics, and hyperparameter tuning (supervised/unsupervised).</p></li><li><p>
Data prep &amp; analysis: ETL/EDA, data cleaning, handling missing/outliers, and building insight narratives with visuals.</p></li></ul></li></ul></div>

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