senior scientist

<div>
 
 Job Description
 
 
 
 
 Your Responsibilities
 
 
 
 As a
 
 Senior Scientist
 
 , you will play a key role in supporting our beverage application laboratory and contributing to the development of finished applications. You will take ownership of customer projects, ensuring all activities are delivered in line with timelines, safety standards, and business objectives.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Develop a strong understanding of ADM Nutrition&rsquo;s product and service portfolio
 </li>
 <li>
 Be responsible for the creation, production, and adaptation of taste samples, including modifications of ADM products based on customer requirements and releasing samples for customer evaluation
 </li>
 <li>
 Work confidently with fine chemicals while maintaining precise, disciplined, and safe working practices
 </li>
 <li>
 Collaborate cross-functionally across EMEA, including with our development headquarters in Germany, other application laboratories, and commercial teams
 </li>
 <li>
 Coordinate multiple customer projects simultaneously while ensuring efficient project execution and communication
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Food Science &amp; Technology, Chemistry, Pharmacy, or a related field
 </li>
 <li>
 Minimum 5 years of experience in beverage product development and applications
 </li>
 <li>
 Proven success working within a B2B environment
 </li>
 <li>
 Strong knowledge of product processing and ingredient interactions
 </li>
 <li>
 Excellent project management skills with the ability to manage multiple priorities
 </li>
 <li>
 Excellent written and spoken English and Arabic
 </li>
 <li>
 Strong communication and stakeholder management skills
 </li>
 <li>
 Good IT skills with experience using tools such as SAP and Salesforce
 </li>
 <li>
 Passion for developing innovative solutions and staying ahead of beverage market trends
 </li>
 <li>
 Collaborative mindset with the ability to work effectively across teams and functions
 
 
 </li>
 </ul>
 
 Our Offer
 
 
 
 <ul>
 <li>
 A high level of personal responsibility within a modern and flexible working environment
 </li>
 <li>
 Opportunities for growth and career development, with the possibility to shape your own career path
 </li>
 <li>
 Collaborative colleagues with a strong team spirit who are passionate about solving the nutritional challenges of today and tomorrow
 </li>
 <li>
 Attractive compensation and benefits package, including subsidized health and fitness programs
 </li>
 <li>
 A company culture that promotes continuous learning, inclusion, and diversity across all functions and levels
 
 
 </li>
 </ul>
 
 #IncludingYou
 
 
 
 Diversity, equity, inclusion and belonging are cornerstones of ADM&rsquo;s efforts to continue innovating, driving growth, and delivering outstanding performance. We are committed to attracting and retaining a diverse workforce and create welcoming, truly inclusive work environments &mdash; environments that enable every ADM colleague to feel comfortable on the job, make meaningful contributions to our success, and grow their career. We respect and value the unique backgrounds and experiences that each person can bring to ADM because we know that diversity of perspectives makes us better, together.
 
 
 For more information regarding our efforts to advance Diversity, Equity, Inclusion &amp; Belonging, please visit our website here: Culture, Engagement &amp; Inclusion | ADM.
 
 
 
 About ADM
 
 
 
 At ADM, we unlock the power of nature to provide access to nutrition worldwide. With industry-advancing innovations, a complete portfolio of ingredients and solutions to meet any taste, and a commitment to sustainability, we give customers an edge in solving the nutritional challenges of today and tomorrow. We&rsquo;re a global leader in human and animal nutrition and the world&rsquo;s premier agricultural origination and processing company. Our breadth, depth, insights, facilities and logistical expertise give us unparalleled capabilities to meet needs for food, beverages, health and wellness, and more. From the seed of the idea to the outcome of the solution, we enrich the quality of life the world over. Learn more at www.adm.com.
 
 
 
 Req/Job ID
 
 
 
 109451BR
 
 
 
 Ref ID
 
 
 
</div>

Senior Scientist

DICETEK LLC

<div><h1 class="jobSectionHeader">Role Purpose</h1>
The Senior Data Scientist will lead the development, optimization, and deployment of advanced card fraud detection models for issuing and acquiring businesses. This role involves end-to-end model lifecycle management, including training, hosting, evaluation, and deployment using SAS SFD and modern MLOps practices. The candidate will work closely with fraud risk, data engineering, and technology teams to ensure robust, scalable, and high-performing solutions.<h1 class="jobSectionHeader">
Key Responsibilities</h1><ul><li>Card Fraud Model Development &amp; Optimization: Design, develop, and optimize card fraud detection models for issuing and acquiring portfolios. Implement advanced statistical, machine learning, and AI techniques to improve fraud detection accuracy and precision and minimizing false positives.</li><li>Model Hosting &amp; Deployment: Deploy models using SAS SFD and integrate with production systems. Ensure seamless hosting and scalability of models across multiple environments.</li><li>MLOps &amp; Automation: Establish and maintain MLOps pipelines for continuous integration, deployment, and monitoring of fraud models. Automate model retraining and performance tracking processes.</li><li>Evaluation &amp; Testing: Conduct rigorous model validation, stress testing, and performance benchmarking. Collaborate with fraud operations teams to ensure models meet business and regulatory requirements.</li><li>Collaboration &amp; Stakeholder Management: Partner with fraud risk, data engineers, IT and business teams to deliver end-to-end solutions. Communicate insights and recommendations to senior management and business stakeholders.</li></ul><h1 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h1><ul><li>Education: Master&rsquo;s or Ph.D. in Data Science, Statistics, Computer Science, or related field.</li><li>Technical Skills: Strong proficiency in SAS (including SAS SFD), Python, and SQL. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD pipelines). Deep understanding of card fraud detection techniques and transaction data.</li><li>Experience: 7+ years in data science roles, with at least 3 years in card fraud modeling. Proven track record of deploying models in production environments.</li><li>Soft Skills: Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities.</li></ul><h1 class="jobSectionHeader"> 
Preferred Qualifications</h1><ul><li>Experience in banking or payments industry.</li><li>Familiarity with cloud platforms (AWS, Azure, GCP) for model hosting and deployment.</li><li>Knowledge of regulatory compliance in fraud risk management.</li></ul></div>

Senior Fraud Data Scientist

BCG X

<div>
 Who We Are
 
 
 Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.
 
 
 To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures&mdash;and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.
 
 
 
 We Are BCG X
 
 
 
 We&rsquo;re a diverse team of more than 3,000 tech experts united by a drive to make a difference. Working across industries and disciplines, we combine our experience and expertise to tackle the biggest challenges faced by society today. We go beyond what was once thought possible, creating new and innovative solutions to the world&rsquo;s most complex problems. Leveraging BCG&rsquo;s global network and partnerships with leading organizations, BCG X provides a stable ecosystem for talent to build game-changing businesses, products, and services from the ground up, all while growing their career. Together, we strive to create solutions that will positively impact the lives of millions.
 
 
 What You'll Do
 
 
 Our BCG X teams own the full analytics value-chain end to end: framing new business challenges, designing innovative algorithms, implementing, and deploying scalable solutions, and enabling colleagues and clients to fully embrace AI. Our product offerings span from fully custom-builds to industry specific leading edge AI software solutions.
 
 
 As a Data Scientist and Senior Data Scientist, you'll be part of our rapidly growing team. You'll have the chance to apply data science methods and analytics to real-world business situations across a variety of industries to drive significant business impact. You'll have the chance to partner with clients in a variety of BCG regions and industries, and on key topics like climate change, enabling them to design, build, and deploy new and innovative solutions.
 
 
 Additional responsibilities will include developing and delivering thought leadership in scientific communities and papers as well as leading conferences on behalf of BCG X. Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative.
 
 
 We Are Looking For Talented Individuals With a Passion For Data Science, Statistics, Operations Research And Transforming Organizations Into AI Led Innovative Companies. Successful Candidates Possess The Following
 
 
 <ul>
 <li>
 Comfortable in a client-facing role with the ambition to lead teams
 </li>
 <li>
 Likes to distill complex results or processes into simple, clear visualizations
 </li>
 <li>
 Explain sophisticated data science concepts in an understandable manner
 </li>
 <li>
 Love building things and are comfortable working with modern development tools and writing code collaboratively (bonus points if you have a software development or DevOps experience)
 </li>
 <li>
 Significant experience applying advanced analytics to a variety of business situations and a proven ability to synthesize complex data
 </li>
 <li>
 Deep understanding of modern machine learning techniques and their mathematical underpinnings, and can translate this into business implications for our clients
 </li>
 <li>
 Have strong project management skills
 
 
 </li>
 </ul>
 What You'll Bring
 
 
 
 Technologies
 
 
 
 Programming Languages: Python
 
 
 #BCGXjob
 
 
 Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws.
 
 
 BCG is an E - Verify Employer. Click here for more information on E-Verify.
</div>

Forward Deployed AI Scientist, United Arab Emirates - BCG X

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

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

talabat

<div>
 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>

Explore 240+ Senior scientist in Dubai this July. Find roles across top companies and apply now to boost your career.

240 senior scientist jobs In Dubai

Senior Scientist

Senior Fraud Data Scientist

Senior Fraud Data Scientist

Forward Deployed AI Scientist, United Arab Emirates - BCG X

Data Platform Lead

Data Scientist II - Analysis, QC

Data Scientist II - Analysis, QC