data analyst

Udrive

<div>
 
 Udrive
 
 is seeking a detail-oriented and motivated Junior Data Analyst to support cross-functional analytics needs for our business. This role will assist our analytics team in managing operational reporting, automating workflows, conducting exploratory analyses, and ensuring data integrity across platforms.
 
 
 You&rsquo;ll work closely with business teams including Operations, Product, Marketing, and Customer Service to deliver data-driven insights and maintain reporting excellence.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Reporting, Analysis Visualization: Build and maintain recurring reports and dashboards using Tableau Excel, and internal tools.
 </li>
 <li>
 Track key performance indicators (KPIs) across fleet, operations, marketing, and business lines.
 </li>
 <li>
 Assist in visual storytelling and communicating insights to stakeholders in a clear, digestible format.
 </li>
 <li>
 Conduct exploratory and ad-hoc analyses to support initiatives like fleet optimization, customer segmentation, marketing initiatives.
 </li>
 <li>
 Collaborate with marketing, product, engineering to derive actionable insights from raw datasets.
 </li>
 <li>
 Support the automation of recurring data processes using SQL, Python
 </li>
 <li>
 Data Quality Governance: Perform data audits to ensure consistency, accuracy, and completeness. Identify and flag anomalies, track data lineage, and maintain documentation for analytics workflows.
 </li>
 <li>
 Document Data Processes, Dashboards Requests
 </li>
 <li>
 Collaboration Support Partner with stakeholders in Operations, Marketing, Product, and CS to address analytical requests and performance queries.
 </li>
 <li>
 Help train teams in reading dashboards and interpreting KPIs.
 
 
 </li>
 </ul>
 
 Qualifications Skills
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Data Science, Computer Science, Engineering, or a related field.
 </li>
 <li>
 0&ndash;2 years of experience in a data analyst or business analyst role.
 </li>
 <li>
 Proficiency in SQL and working knowledge of Python (Pandas, NumPy, etc.).
 </li>
 <li>
 Experience with data visualization (Tableau, Power BI, SuperSet) Strong Excel/Google Sheets skills.
 </li>
 <li>
 Comfortable working with large datasets and drawing actionable insights.
 </li>
 <li>
 Detail-oriented, with a problem-solving mindset and a proactive attitude.
 </li>
 <li>
 Preferred Skills Exposure to SuperSet, GA4, NoSQL, CAC, LTV Jira, Confluence
 </li>
 <li>
 Understanding of business metrics in the mobility, logistics, or SaaS industry is a plus.
 </li>
 <li>
 Ability to work in a fast-paced startup environment.
 </li>
 <li>
 Understanding and experience of data pipelines / ETL concepts is preferred.
 </li>
 </ul>
</div>

Junior Data Analyst

The University of Manchester - Dubai

<div>
 
 
 Overall, Purpose of the Job
 
 
 
 The Institutional Data &amp; Regulatory Compliance Analyst is responsible for the administration, governance, quality, and integration of institutional data systems at UoM-Dubai. The role provides dedicated ownership of all regulatory data reporting requirements, including MoHESR and KHDA obligations, with particular focus on:
 
 
 &bull;&nbsp;&nbsp;HEDB/CHEDS dataset preparation, validation, and submission across all reporting cycles
 
 
 &bull;&nbsp;&nbsp;OBEF KPI data collection, calculation, evidence compilation, and submission across all 24 KPIs spanning Employment Outcomes, Learning Outcomes, Industry Collaboration, Research Outcomes, Reputation, and Community Engagement
 
 
 &bull;&nbsp;&nbsp;&nbsp;API integration readiness for the transition from portal-based HEDB submission to MoHESR's master API framework
 
 
 &bull;&nbsp;&nbsp;&nbsp;Effective administration of Educore and related institutional applications
 
 
 &bull;&nbsp;&nbsp;&nbsp;Supporting institutional compliance with CAA, MoHESR, and KHDA requirements
 
 
 &nbsp;
 
 
 This role is critical as MoHESR transitions to an outcome-based evaluation model assessed across 24 KPIs, requiring sustained, specialist data ownership that cannot be absorbed within existing operational roles.
 
 
 
 
 
 Key Responsibilities
 
 <ol>
 <li>
 
 OBEF Data Management and KPI Reporting
 
 </li>
 </ol>
 
 The postholder will take lead responsibility for OBEF data collection, calculation, and submission across all six pillars:
 
 
 &bull;&nbsp;&nbsp;Coordinate and validate data for all 24 OBEF KPIs at institutional and programmatic level, including Employment Rate, Retention Rate (FYR), Assessment Quality Review, Work Placement Participation, Joint Industry Courses, Publication Ratio, International Accreditation Status, and Community Engagement indicators
 
 
 &bull;&nbsp;Manage rolling calculation cycles &mdash; 3-year rolling averages for employment and retention KPIs; 5-year averages for research and collaboration KPIs; cumulative totals for IP and research impact
 
 
 &bull;&nbsp;Coordinate graduate employment tracking processes including the 12-month post-graduation employment survey, internship-to-employment conversion rates, and relevant job classification in line with MoHESR definitions
 
 
 &bull; Maintain KPI evidence packages including employer feedback forms, work placement completion records, micro credential and professional license registers, student satisfaction data, and industry contribution records
 
 
 &bull; Prepare OBEF scorecard submissions and support institutional and programmatic performance monitoring against OBEF thresholds
 
 
 &bull;&nbsp;Liaise with academic and professional services teams to collect, validate, and reconcile OBEF data inputs across faculties and support functions
 
 
 
 
 
 
 2.HEDB / CHEDS Regulatory Reporting
 
 
 
 
 &bull;
 
 Coordinate the preparation, validation, and submission of all HEDB datasets required by MoHESR across reporting cycles, including student enrolment, academic outcomes, graduation, and research data
 
 
 &bull;&nbsp;Manage CHEDS-to-HEDB transition workflows and ensure submission readiness in line with MoHESR's evolving portal requirements
 
 
 &bull;&nbsp;Validate HEDB datasets for completeness, accuracy, and consistency with institutional records held in Educore and related systems
 
 
 &bull;&nbsp;Maintain submission logs, data quality records, and audit trails for all HEDB reporting cycles
 
 
 &bull;&nbsp;Monitor MoHESR portal updates, deadline schedules, and data specification changes and ensure timely institutional responses
 
 
 &bull;&nbsp;Support CAA reporting obligations that draw on overlapping HEDB data sources
 
 
 
 
 
 
 3.Application and System Administration
 
 
 
 &bull;&nbsp;Manage the day-to-day administration of Educore and other relevant institutional applications, including user access, role-based permissions, and validation rules
 
 
 &bull;&nbsp;Monitor system functionality, data integrity, and operational performance across institutional data platforms
 
 
 &bull;&nbsp;Coordinate system updates, testing, enhancements, and release of new functionality with vendors and internal stakeholders
 
 
 &bull;&nbsp;Support issue resolution and escalation relating to application performance and data system functionality
 
 
 &bull;&nbsp;&nbsp;Maintain Educore data configurations to support OBEF and HEDB data extraction workflows
 
 
 &nbsp;
 
 
 
 4.API Integration and Technical Readiness
 
 &nbsp;
 
 
 &nbsp;&bull;&nbsp;Lead institutional readiness for MoHESR's transition from HEDB portal submission to master API-based data exchange, coordinating endpoint mapping, testing, and implementation activities
 
 
 &bull;&nbsp;Support KHDA API integration requirements, including technical coordination, data mapping, and post-implementation monitoring
 
 
 &bull;&nbsp;Liaise with Home Campus IT, MoHESR technical teams, KHDA API teams, and Educore to ensure system-to-system data exchange is accurate, secure, and compliant
 
 
 &bull;&nbsp;Document institutional data architecture, API workflows, system interfaces, and integration arrangements
 
 
 &bull;&nbsp;&nbsp;Support pilot testing, rollout, and post-implementation monitoring of new integrations
 
 
 
 
 
 
 5.Data Quality, Validation, and Reconciliation
 
 
 
 &bull;&nbsp;Carry out data validation, reconciliation, and quality assurance checks across Educore, HEDB, OBEF datasets, and supporting evidence registers
 
 
 &bull;&nbsp;Identify data gaps, inconsistencies, and quality issues and coordinate corrective actions with relevant teams
 
 
 &bull;&nbsp;Maintain data quality logs, issue registers, and improvement action records
 
 
 &bull;&nbsp;Support standardization of reporting processes to reduce reliance on manual workarounds and ad hoc data extractions
 
 
 &bull;&nbsp;Develop and maintain data dictionaries, reporting logic documentation, and KPI calculation guides aligned to MoHESR OBEF definitions
 
 
 
 
 
 
 6.Stakeholder Liaison and Regulatory Coordination
 
 
 
 &bull;&nbsp;Act as the primary operational point of contact for data systems, OBEF reporting, HEDB submissions, and API integration matters
 
 
 &bull;&nbsp;Liaise with MoHESR data and technical teams, KHDA regulatory and API teams, CAA, Educore, and Home Campus IT
 
 
 &bull;&nbsp;Coordinate technical clarifications, regulatory follow-up actions, and issue resolution with external stakeholders in a timely and professional manner
 
 
 &bull;&nbsp;Ensure institutional responses to regulators and system partners are accurate, consistent, and properly documented
 
 
 
 
 
 
 7.Documentation, Audit, and Compliance Support
 
 
 
 &bull;&nbsp;Maintain up-to-date SOPs, user guides, OBEF evidence registers, HEDB submission records, integration documentation, and system administration logs
 
 
 &bull;&nbsp;Support audit readiness by ensuring availability of records, evidence trails, and compliance documentation for MoHESR, KHDA, and CAA
 
 
 &bull;&nbsp;Contribute to inspection preparation by providing clear evidence of data governance, KPI validation controls, reporting practices, and system management
 
 
 &bull;&nbsp;Support the implementation of secure and compliant data handling practices in line with institutional and Home Campus requirements
 
 
 
 
 
 
 Role Specification
 
 
 
 &nbsp;
 
 Essential Qualifications
 
 
 
 &bull;&nbsp;Bachelor&rsquo;s degree in information systems, Data Management, Computer Science, Business Information Systems, or a related field
 
 
 
 
 
 
 Essential Knowledge and Experience
 
 
 
 &bull;&nbsp;Experience administering institutional applications, databases, or student information systems
 
 
 &bull;&nbsp;Experience in data reporting, validation, reconciliation, and quality assurance
 
 
 &bull;&nbsp;Experience working with complex datasets, multi-cycle reporting requirements, and cross-functional stakeholders
 
 
 &bull;&nbsp;Experience coordinating with internal and external technical teams, vendors, or service providers
 
 
 &bull;&nbsp;Understanding of system integrations, APIs, and data workflows
 
 
 &bull;&nbsp;Experience maintaining system documentation, audit trails, and operational records
 
 
 &bull;&nbsp;Strong working knowledge of Excel and data reporting tools
 
 
 
 
 
 
 Desirable Knowledge and Experience
 
 
 
 &bull;&nbsp;Experience within UAE higher education or another regulated sector
 
 
 &bull;&nbsp;Familiarity with MoHESR regulatory frameworks, including OBEF (24-KPI framework), HEDB/CHEDS submission processes, and CAA reporting requirements
 
 
 &bull;&nbsp;Understanding of OBEF KPI definitions, data sources, calculation methodologies, and evidence requirements across all six pillars (Employment, Learning, Industry Collaboration, Research, Reputation, Community Engagement)
 
 
 &bull;&nbsp;Familiarity with KHDA regulatory reporting and API integration frameworks
 
 
 &bull;&nbsp;Experience working with dashboard reporting, compliance monitoring, or institutional data governance frameworks
 
 
 &bull;&nbsp;Experience supporting role-based access controls, Row-Level Security, or similar access management arrangements
 
 
 &bull;&nbsp;Familiarity with Educore or comparable student records and compliance platforms
 
 
 &bull;&nbsp;Understanding of MoHESR's transition from portal-based HEDB submission to master API integration
 
 
 
 
 
 
 Skills and Competencies
 
 
 
 &bull;&nbsp;Strong analytical and problem-solving skills with the ability to interpret complex regulatory data requirements
 
 
 &bull; High attention to detail and accuracy in data validation and reporting
 
 
 &bull;&nbsp;Ability to manage multiple reporting cycles, deadlines, and priorities simultaneously
 
 
 &bull;&nbsp;Strong communication and stakeholder management skills across operational, technical, and regulatory functions
 
 
 &bull;&nbsp;Ability to translate technical data issues into clear operational and regulatory language
 
 
 &bull;&nbsp;Strong organizational skills and ability to maintain accurate records, evidence registers, and documentation
 
 
 &bull;&nbsp;Professional judgement, discretion, and accountability in handling institutional data
 
 
 
 
 
 
 Key Regulatory Context
 
 
 rameworkelevance to This Role
 
 
 
 
 OBEF (MoHESR)
 
 
 
 24 KPIs across 6 pillars. Institutional and programmatic scoring. Rolling 3- and 5-year calculations. Transitioning to master API submission.
 
 
 
 HEDB / CHEDS
 
 
 
 MoHESR's Higher Education Database. Multi-cycle student data submissions covering enrolment, outcomes, and graduation. Feeds directly into OBEF KPI calculations.
 
 
 
 KHDA
 
 
 
 Dubai regulator. API integration and institutional dashboard reporting. Requires dedicated technical and data liaison.
 
 
 
 CAA
 
 
 
 Commission for Academic Accreditation. Accreditation and quality reporting that draws on overlapping OBEF and HEDB data sources.
 
 
 
 Master API
 
 
 
 MoHESR's long-term data submission infrastructure replacing HEDB portal and CAA manual submissions. Requires institutional API readiness and integration coordination.
 
</div>

Institutional Data Regulatory Compliance Analyst

Kpler

<div>
 At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.
 
 
 Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 700 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.
 
 
 
 Your future position
 
 
 
 Kpler&rsquo;s Oil &amp; Chemicals business unit is rapidly advancing its real-time analytics and is looking for a technically sharp, data-literate Refineries Analyst to join its growing global team.
 
 
 In this role, you will take absolute ownership of the data integrity, maintenance, and quality control of our bottom-up refinery models. You will synthesize Kpler&rsquo;s industry-leading proprietary data-including live crude flows, production, pipeline volumes, and inventory levels-into a cohesive modeling framework, utilizing our internal Linear Programming (LP) model as a core tool for tuning and optimization. By connecting upstream inputs and offline events with real-world refinery capacities and yields, you will ensure our models seamlessly integrate into Kpler&rsquo;s broader Supply &amp; Demand balances.
 
 
 Because you are joining us during an ambitious product expansion, you will play a foundational role in the evolution of our platform. This is a truly hybrid-minded position where you will serve as the subject matter expert bridging the gap between physical market reality and technical architecture-partnering closely with our Product Engineering team to build, refine, and validate our most sophisticated fundamental datasets.
 
 
 
 Your Mission Is To
 
 
 
 <ul>
 <li>
 Maintain data integrity, capacity, and offline event records for individual refinery models and regional balances, utilizing the internal Linear Programming model for tuning.
 </li>
 <li>
 Prioritize the validation and improvement of existing models; data quality and domain expertise are the critical drivers for this role.
 </li>
 <li>
 Lead the effort to backtest and guide models using external data sources (EIA, JODI, IRR, ANP) to ensure outputs align with physical market realities.
 </li>
 <li>
 Apply a deep understanding of distillation, reforming, FCC, and blending to optimize refinery circuit views and regional supply/demand dynamics.
 </li>
 <li>
 Source and leverage large datasets using Python, PostgreSQL and to automate data flows and improve model accuracy.
 </li>
 <li>
 Collaborate with Data, Product, Engineering, and Sales teams to provide insights for refineries product development.
 </li>
 <li>
 Respond to internal and external data requests and client queries in a timely manner.
 
 
 </li>
 </ul>
 
 Essential
 
 
 
 
 Experience &amp; Background
 
 
 
 <ul>
 <li>
 At least 3&ndash;5 years of experience as a Refinery Economist, Refining Analyst, LP Modeler or related roles.
 </li>
 <li>
 A deep understanding of physical refinery unit operations (Distillation, Reforming, FCC, Blending, etc.) and refinery economics (flows, pricing, regulations, and arbitrage dynamics).
 </li>
 <li>
 Practical experience using industry-standard Linear Programming software (Aspen PIMS, AVEVA Unified/Spiral, or Haverly GRTMPS) is essential to be functional in this role.
 </li>
 <li>
 Comfortable with Python and PostgreSQL
 </li>
 <li>
 Proven experience sourcing and leveraging external data (EIA/JODI/IRR) to model refineries.
 </li>
 <li>
 Strong background in data-driven modeling, validation, and managing input data integrity (e.g., capacity and offline events).
 
 
 </li>
 </ul>
 
 Desirable
 
 
 
 <ul>
 <li>
 Experience with refinery optimization, especially with a focus on circuit-wide views.
 </li>
 <li>
 Experience with data visualization.
 </li>
 <li>
 Past experience contributing to SaaS product or data improvement initiatives.
 </li>
 <li>
 Experience in leveraging AI tools (Claude, Cursor, etc) for data analysis &amp; management, and general workflow optimization
 
 
 </li>
 </ul>
 
 Behavioural Competencies
 
 
 
 <ul>
 <li>
 Ownership of day-to-day work and strong attention to detail.
 </li>
 <li>
 Self-starter, thrives in an ambitious, early-stage product environment without requiring direct supervision.
 </li>
 <li>
 Eagerness to invest significant time in individual refinery tuning and bottom-up modeling.
 </li>
 <li>
 Driven to find data to backtest and guide models.
 </li>
 <li>
 Client-facing confidence.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in a technical or quantitative field, with proven experience applying modeling techniques in commercial or research environments
 
 
 </li>
 </ul>
 We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you&rsquo;ve found your ideal destination. Are you ready to embark on this exciting journey with us?
 
 
 
 We make things happen
 
 
 
 We act decisively and with purpose, going the extra mile.
 
 
 
 We build together
 
 
 
 We foster relationships and develop creative solutions to address market challenges.
 
 
 
 We are here to help
 
 
 
 We are accessible and supportive to colleagues and clients with a friendly approach.
 
 
 
 Our People Pledge
 
 
 
 Don&rsquo;t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don&rsquo;t match 100% of the job requirements. Don&rsquo;t let the confidence gap stand in your way, we&rsquo;d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.
 
 
 Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.
</div>

Refineries Analyst

The Emirates Group

<div><h5 class="jobSectionHeader">Job Purpose
</h5>At Emirates, we believe in connecting the world, to and through, our global hub in Dubai; and in constantly innovating to ensure our customers &lsquo;Fly Better&rsquo;. Emirates is a global leader in the aviation industry, known for its exceptional customer service and cutting-edge technology. Based in Dubai, the airline operates a vast network of international flights, offering passengers unparalleled comfort and convenience. As part of the Emirates Group, the company is committed to delivering innovative solutions and creating memorable travel experiences. With a strong focus on customer satisfaction, Emirates integrates modern communication channels to enhance service delivery across all touchpoints. The airline continues to set industry standards in operational excellence, sustainability, and digital transformation, ensuring that it remains a top choice for travellers worldwide.
As a Resource Planning Officer you will ensure maximum network resource productivity and efficiency by use of resource planning in order to achieve targeted service levels. Maximise the value of the data held in the systems by analysing it, using innovative methods, requirements of management and extract insights using creative data mining approaches.
In this role, you will:
<div><ul><li>Work as part of team and follow established operating standard and procedures to meet requirements with high quality outputs and contribute to the division achieving its goals.
</li><li>Communicate regularly with Contact centre operations teams to identify report/schedule requirements and adherence issues and their impact on the business.
</li><li>Create a plan of action to maintain network and contact centre service levels.
</li><li>Have a thorough knowledge of Corporate Emergency Response policies and procedures to ensure immediate activation, when required, during an unforeseen event.
</li><li>Participate in a rotating remote support team for Global Connect to ensure 24x7 coverage across the network, in relation to technical and operational incidents.
</li><li>Develop weekly roster on agreed cycles ensuring schedules optimise available resources. Develop interaction forecasts, annual leave and training plans based on strategic direction established GCRPT for each contact centre ensuring each area has adequate staff to meet service levels. Produce and maintain employee schedules which ensure that targeted service levels are achieved.
</li><li>Liaise with Contact Centre Operations Officers and local management teams to manage holiday planning, agent change of hours requests and leave allocation so as to maintain high employee satisfaction without compromising on customer service.
</li><li>Use developed forecasts to identify gaps in operational coverage with current manpower and recommend overtime requirements, ensuring adherence to employee legislation for the respective jurisdiction for the next 2 weeks ahead.
</li><li>Proactively address shift and daily operational productivity and manage and troubleshoot immediate operational issues in order to maintain network service levels and to ensure impact on customer service across the contact centre and retail office network is kept to a minimum.
</li><li>Monitor recruitment and attrition rates and highlight potential issues to the Contact Centre Operations team and training departments to ensure adequate resources is recruited and competent in appropriate skills.
</li><li>Produce regular communication newsletters to the network updating them on annual leave availability and potential resource surplus and shortfall periods.
</li></ul></div><h5 class="jobSectionHeader">Qualification
</h5>To be considered for the role, you must meet the below requirements:
<div><ul><li>Working experience as a Resource Planner/ Data Analyst within Aviation Industry or Contact Centre.
</li><li>Ability to work as a sole contributor &amp; as a team player to meet tight deadlines.
</li><li>Deliver strong results within a virtual team environment.
</li><li>Ability to build enduring relationships within the business.
</li><li>Advanced knowledge in MS Excel (Macro, Pivot tables etc.)
</li><li>Advanced knowledge in PowerPoint.
</li><li>Working knowledge of databases like SAP, Micro Strategy, SQL servers etc.
</li></ul></div>Emirates Group is an international organisation with employees from over 170 nationalities; we encourage applications from across the globe. Your application journey begins by applying via the Emirates Group Careers website. Please ensure your CV is up to date for our talent acquisition team to review your profile. If you meet the criteria of the role, you will then be invited to complete a HireVue video interview, to share more about your experience and your career aspirations. If you are shortlisted, you will then be invited to interview with our hiring managers. If you are successful, your recruiter will reach out to you with an offer and then our Onboarding team will ensure a smooth transition to your new role at Emirates Group.
<h5 class="jobSectionHeader">Salary &amp; benefits
</h5>Join us in Dubai and enjoy attractive salary and travel benefits that are exclusive to our industry, including discounts on flights and hotels stays around the world. You can find out more information about our employee benefits in the Working Here section of our website www.emirates.com/careers. Further information on what&rsquo;s it like to live and work in our cosmopolitan home city, can be found in the Dubai Lifestyle section.</div>

Resource Planning Officer

Dicetek LLC

<div>
 
 Summary Of Role
 
 
 
 <ul>
 <li>
 Co-development of analytical engines based on statistical and machine learning algorithms
 </li>
 <li>
 Creation of sustainable digital solutions integrated with existing IT infrastructure in collaboration with business
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Conducts analytical experiments methodically with guidance from technology lead to help solve various problems and make a true impact across multiple domains and situations
 </li>
 <li>
 Process relevant data sources and build clear data-cleaning pipelines to feed data points and variables to the models in a well-structured format
 </li>
 <li>
 Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy for visualization to business
 </li>
 <li>
 Analyze data for trends and patterns, apply statistical and machine learning algorithms, and interpret data with a clear objective in mind in line with project goals and milestones
 </li>
 <li>
 Support the deployment of analytical models into existing IT infrastructure by collaborating with DevOps engineers and Product owners
 </li>
 <li>
 Maintain delivered solutions sustainability after the development phase
 
 
 </li>
 </ul>
 
 ﻿Required Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in information systems, data analytics, data science, computer science, economics, risk management or another quantitative related field
 </li>
 <li>
 Experience with Excel, SQL, Python, basic BI-development
 </li>
 <li>
 Proficiency in data processing (Pandas), statistical analysis, and machine learning algorithms
 </li>
 <li>
 Knowledge in building data processing pipelines &amp; ETLs
 </li>
 <li>
 Experience in implementing predictive engines with a focus on time-series forecast
 </li>
 <li>
 Experience in writing API calls based on specifications
 </li>
 <li>
 Experience in automated testing, ability to write mock and unit tests to test both model inputs and outputs
 </li>
 <li>
 Effective collaboration, experience in working with Scrum/Agile teams &amp; task tracking
 
 
 </li>
 </ul>
 
 Additional Considerations
 
 
 
 <ul>
 <li>
 The preferred profile is "all-the-way-rounder" rather than a person with deep expertise in only something specific
 </li>
 </ul>
</div>

Data Scientist (Arabic Speaker)

DICETEK LLC

<div>Summary of role<ul><li>Co-development of analytical engines based on statistical and machine learning algorithms</li><li>Creation of sustainable digital solutions integrated with existing IT infrastructure in collaboration with business</li></ul>
Responsibilities<ul><li>Conducts analytical experiments methodically with guidance from technology lead to help solve various problems and make a true impact across multiple domains and situations</li><li>Process relevant data sources and build clear data-cleaning pipelines to feed data points and variables to the models in a well-structured format</li><li>Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy for visualization to business</li><li>Analyze data for trends and patterns, apply statistical and machine learning algorithms, and interpret data with a clear objective in mind in line with project goals and milestones</li><li>Support the deployment of analytical models into existing IT infrastructure by collaborating with DevOps engineers and Product owners</li><li>Maintain delivered solutions sustainability after the development phase</li></ul> 
﻿Required Qualifications &amp; experience<ul><li>Bachelor's or Master's degree in information systems, data analytics, data science, computer science, economics, risk management or another quantitative related field</li><li>Experience with Excel, SQL, Python, basic BI-development</li><li>Proficiency in data processing (Pandas), statistical analysis, and machine learning algorithms</li><li>Knowledge in building data processing pipelines &amp; ETLs</li><li>Experience in implementing predictive engines with a focus on time-series forecast</li><li>Experience in writing API calls based on specifications</li><li>Experience in automated testing, ability to write mock and unit tests to test both model inputs and outputs</li><li>Effective collaboration, experience in working with Scrum/Agile teams &amp; task tracking</li></ul>
Additional considerations<ul><li>The preferred profile is &quot;all-the-way-rounder&quot; rather than a person with deep expertise in only something specific</li></ul></div>

Delivery Hero

<div>Company Description 
Since launching in Kuwait in 2004, talabat has become the region&rsquo;s leading on-demand delivery app, serving millions of customers across eight countries. Our Quick Commerce (QC) Hub powers the grocery and convenience delivery experience &mdash; getting everyday essentials to customers&rsquo; doors in minutes, not hours.
Behind every delivery is data. Our QC data team works at a scale most data scientists only read about: millions of daily transactions, thousands of partners, and decisions that directly shape how people across the Middle East get their groceries delivered. We&rsquo;re building an analytics-first culture where every product and business decision is grounded in evidence. 
Job Description 
Why This Role
As a Data Scientist on the QC Hub team, you&rsquo;ll be the analytical brain behind one of talabat&rsquo;s fastest-growing verticals. You won&rsquo;t just crunch numbers &mdash; you&rsquo;ll partner directly with product and business leaders to shape strategy, design experiments that affect millions of users, and build the data foundations that power smarter decisions.
This is a role for someone who loves turning messy, ambiguous business questions into clean, actionable analysis &mdash; and who gets energy from seeing their insights change how a team operates.
What Success Looks Like<ul><li>
First 90 days: You&rsquo;ve ramped up on your domain, built relationships with your product and business partners, understood the data landscape, and delivered your first actionable analysis.</li><li>
By 6 months: You&rsquo;re the go-to analytical partner for your domain. You&rsquo;re independently designing and running experiments, and stakeholders regularly act on your recommendations.</li><li>
By 12 months: Your work has measurably improved decision quality in your domain. You&rsquo;ve built or refined data models that the team relies on daily, and you&rsquo;re mentoring newer team members on analytical best practices.</li></ul>
What You&rsquo;ll Actually Do
You&rsquo;ll spend roughly:<ul><li>
40% on deep analysis and experimentation &mdash; designing A/B tests, running multivariate experiments, doing deep dives into performance drivers, and turning findings into clear recommendations.</li><li>
30% on data modelling and quality &mdash; building and maintaining the data models that let us measure what matters, profiling source data, and ensuring data reliability.</li><li>
30% working with stakeholders &mdash; partnering with product and business managers to frame the right questions, set meaningful KPIs, and present insights that drive action.</li></ul>
Day-to-day, you&rsquo;ll:<ul><li>
Turn ambiguous business questions into structured analytical problems</li><li>
Build and maintain dimensional data models in BigQuery</li><li>
Design, execute, and interpret experiments (A/B and multivariate)</li><li>
Create automated dashboards and reports that stakeholders actually use</li><li>
Challenge assumptions with data &mdash; including your own</li><li>
Collaborate with data engineers on logging and data pipeline quality</li></ul>
You&rsquo;ll Thrive Here If You&hellip;<ul><li>
Love being embedded with business teams, not siloed in a data team</li><li>
Get satisfaction from changing how decisions are made, not just producing reports</li><li>
Are comfortable with ambiguity &mdash; many of your best projects will start as vague questions</li><li>
Care deeply about data quality and are willing to dig into source systems to understand what the data actually means</li><li>
Communicate clearly with non-technical stakeholders</li></ul>
This Might Not Be For You If You&hellip;<ul><li>
Want to build ML models full-time (this role is analytics and experimentation focused)</li><li>
Prefer working independently without regular stakeholder interaction</li><li>
Need clearly defined problems handed to you</li><li>
Are more interested in tools and techniques than business impact</li></ul> 

Qualifications 
What You Bring 
Education
Degree in a quantitative field (statistics, mathematics, economics, computer science, engineering, or similar) &mdash; or equivalent practical experience. A postgraduate degree is a plus but not required.
Must-Haves:<ul><li>
Strong SQL skills &mdash; you can write complex queries with window functions, CTEs, and optimise for performance on large datasets</li><li>
Reproducible analysis in Python or R &mdash; you write clean, well-structured analytical code, not one-off scripts</li><li>
Experiment design expertise &mdash; you understand when to use A/B vs. multivariate tests, can calculate sample sizes, and know the pitfalls of statistical testing</li><li>
Full analysis lifecycle experience &mdash; from problem framing through data auditing, analysis, interpretation, and presenting recommendations</li><li>
Data modelling knowledge &mdash; you understand dimensional design and can build models that serve both ad-hoc analysis and automated reporting</li><li>
Product analytics intuition &mdash; you&rsquo;re familiar with metrics like conversion, engagement, and retention, and know how to measure product health</li><li>
3+ years in data science, analytics, or a related quantitative field</li></ul>
Nice-to-Haves:<ul><li>
Experience with BigQuery and Google Cloud Platform</li><li>
Data engineering skills (Airflow, dbt, or similar pipeline tools)</li><li>
Experience with ML frameworks (Scikit-learn, XGBoost, LightGBM)</li><li>
Familiarity with modern data tools and AI-assisted analysis workflows</li><li>
Experience in an online consumer product or marketplace environment</li></ul> 

Additional Information 
What We Offer<ul><li>
Impact at scale &mdash; your work directly affects how millions of people get their daily essentials</li><li>
An analytics-first culture &mdash; a data team that&rsquo;s genuinely invested in analytical excellence, not just dashboarding</li><li>
Modern tooling &mdash; BigQuery, GCP ecosystem, and the freedom to experiment with new approaches including AI-assisted workflows</li><li>
Career growth &mdash; past data scientists on the team have grown into senior individual contributor roles and analytics leads</li><li>
Great Place to Work &mdash; talabat is a certified Great Place to Work across multiple countries in the region</li></ul></div>

Data Scientist II - Analysis, QC

Explore 149+ Data analyst in Dubai this July. Find roles across top companies and apply now to boost your career.

149 data analyst jobs In Dubai

Junior Data Analyst

Institutional Data Regulatory Compliance Analyst

Refineries Analyst

Resource Planning Officer

Data Scientist (Arabic Speaker)

Data Scientist (Arabic Speaker)

Data Scientist II - Analysis, QC