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analytical data scientist

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>

Huspy

<div>
 
 The Story So Far: We&rsquo;re Building a Global Brand in Real Estate
 
 
 
 Huspy is one of the leading property technology companies in EMEA.Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026.
 
 
 Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we&rsquo;ve entered.We&rsquo;ve raised over $140 million (Series A and Series B) from the world&rsquo;s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.
 
 
 We&rsquo;ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world&rsquo;s most traditional industries. We&rsquo;re transforming how property transactions happen &mdash; faster, smarter, and better for everyone.We&rsquo;re not slowing down.
 
 
 The question is: will you be part of what&rsquo;s next?
 
 
 
 The Main Event: What You&rsquo;ll Drive, Build, and Own
 
 
 
 <ul>
 <li>
 Real Estate Market Modeling: Build models applied to challenges such as valuation/pricing leveraging techniques from classic supervised ML to more advanced approaches.
 </li>
 <li>
 Multimodal Embeddings: Create vector representations of Real Estate entities, such as listings, combining images, text, and structured attributes to power search, matching, deduping, or recommendations.
 </li>
 <li>
 Data Analysis &amp; Experimentation: Use SQL/Python to extract, clean, and analyze data; design experiments and evaluate model-product impact with robust metrics.
 </li>
 <li>
 Model Operationalization: Ship models to production with capabilities such as monitoring, automated rollout, or CI/CD (in partnership with engineering).
 </li>
 <li>
 Cross-functional Delivery: Partner with product, engineering, and operations teams to translate business problems into scalable ML solutions.
 
 
 </li>
 </ul>
 
 The Perfect Match: What It Takes to Succeed at Huspy
 
 
 
 <ul>
 <li>
 Proven Experience: 4&ndash;8 years in applied data science/ML, delivering models that move real-world KPIs.
 </li>
 <li>
 SQL &amp; Python Mastery: Strong in frameworks such as Pandas/NumPy/Scikit-learn...building reliable data pipelines, model training and evaluation.
 </li>
 <li>
 MLOps Fundamentals: Experience deploying/maintaining models (batch or real-time), versioning, CI/CD basics, observability, and reproducible training.
 </li>
 <li>
 Communication &amp; Ownership: Clear with technical/non-technical stakeholders; can scope, prioritize, and explain tradeoffs.
 </li>
 <li>
 Comfortable with uncertainty, data quality issues, leakage risks, and market dynamics (location, seasonality, inventory shifts).
 </li>
 <li>
 Nice to Have: Software engineering experience; multimodal/vision experience; voice AI (ASR/NLU) exposure.
 </li>
 <li>
 Academic Background: Bachelor&rsquo;s in STEM (Master&rsquo;s a plus).
 
 
 </li>
 </ul>
 By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
</div>

Data Scientist

The Emirates Group

<div><h5 class="jobSectionHeader">Job Purpose 
</h5> At Emirates Group our Analytics Centre of Excellence (ACoE) is a centralized unit that provides data and analytics support to Emirates Group businesses. This allows our businesses to make better decisions by using data and analytics to understand our customers, operations, and markets.The ACoE is an essential part of Emirates Group's digital transformation strategy. The unit is helping Emirates Group to become a more data-driven organization and to make better decisions by using data and analytics. 
 
As a Data Scientist Team Lead you will manage and drive data science projects through the application of mathematical modelling, machine learning, problem structuring and big data analysis to solve complex business problems across the Emirates Group portfolio. The role will require strong skills in computer science, mathematics, statistics and creative problem solving. The job holder is a focused individual who is able to transcend the world of theory, bring it to life in the business context and collaborate successfully with cross functional teams including academic researchers, business stakeholders and information technology teams. 
 
In this role you will:
<div><ul><li>Manage team of Data Scientists, ensuring the culture, strategy and vision are passed to the teams. Aligned with the DS and EA leadership, review team capabilities and establish training/mentoring plan.
</li><li>Support and drive DS execution within team, targeting and developing relationships with the key internal stakeholders and clients to continue to drive practice demand growth.
</li><li>Derive business insight from large, structured, semi-structured and unstructured, data sets and work with business stakeholders to deploy insights derived from this analysis to extract commercial value.
</li><li>Develop, formulate and execute big data models to solve complex business problems. Research, design, implement and validate cutting-edge algorithms to achieve targeted business outcomes using mathematical models, machine learning, operational research theories and dynamic simulations.
</li><li>Build prescriptive models to identify multi-dimensional trends and patterns to understand our customers, optimise revenue and demand management plus drive efficiencies across the operational environment including aircraft operations, engineering, workforce management and catering.
</li><li>Work with cross-functional team members, combining computer science and mathematics, to identify and inject high-value actionable insights into business processes at their point of highest impact. Work in quick iterations, using the techniques and algorithms best suited for solving the challenging problems of the aviation business.
</li><li>Develop and recommend enhancements to existing tools with the goal of advancing the data science capabilities of the organisation. Perform validation and testing of models to ensure adequacy and reformulate models as necessary.
</li><li>Clearly document and communicate the outcomes of the data science initiatives and make sure that the insights and findings can be clearly understood by business stakeholders and translated into actions.
</li>Inspire and promote the adoption of advanced analytics and data science across the entirety of our organization and provide expertise on mathematical concepts for the broader applied analytics team. 
<li>
</li></ul></div> 
<h5 class="jobSectionHeader">Qualification
</h5>To be considered for the role, you must meet the below requirements:
 Qualifications:
<div><ul><li>MSc/PhD in a relevant field such as data science, operations research, mathematics, science, data mining, artificial intelligence, applied statistics, machine learning or economics.
 </li></ul></div>Experience:
<div><ul><li>7-10+ years of hands-on experience in the Analytics ecosystem including:
</li></ul></div><div><div><div><div><ul><li>Experience Managing Data Science or Analytics Teams or acting as Manager in a consulting company.
</li></ul><ul><li>3-5 years hands-on experience with big data technologies (Spark and Hadoop ecosystem) and deep learning frameworks (Tensorflow, Keras, etc.).
</li></ul><ul><li>5-7 years hands-on experience with SQL, R, Python.
</li></ul><ul><li>2-4 years hands-on experience with DevOps frameworks (Git, CI/CD, Docker).
</li></ul><ul><li>3-5 years hands-on experience building libraries and packages to be re-used by others.
</li></ul><ul><li>3-5 years hands-on experience building DS Solutions for production usage.
</li></ul><ul><li>Team player with a problem-solving attitude.
</li></ul><ul><li>Experience of leading &amp; delivering advanced analytical projects to large, complex organisations in a multi-functional environment.
</li></ul><ul><li>Able to challenge and review the quality and value generated from analytical output.
</li></ul>Focus on driving business value for business clients to support long term relationships. Ability to grow teams, ensuring the culture and strategy gets followed by the new hires. 
<ul><li>
</li></ul></div></div></div></div><div></div> 
Join us in a management role and enjoy an attractive tax-free salary. On top of our generous travel benefits, including discounted flights and hotel stays around the world, this managerial role also has an excellent leave and healthcare package. That&rsquo;s on top of transport benefits, life insurance and more.
<h5 class="jobSectionHeader">Salary &amp; benefits
</h5>Find out what it&rsquo;s like to live and work in our fast-paced, cosmopolitan home city in the Dubai Lifestyle section of our website www.emirates.com/careers</div>

Data Scientist Team Lead –

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)

Bunker Holding A/S

<div>
 
 
 Are you a paid media specialist who thrives on targeting the right audience, optimising campaigns, and turning data into results? Join Bunker Holding Group&rsquo;s international marketing team as Paid Media Specialist in Dubai.
 
 
 
 
 
 
 We are looking for a Paid Media Specialist to support a portfolio of 9+ brands across Bunker Holding Group. You will be part of the marketing team and play a key role in planning, launching, optimising, and reporting on paid media campaigns across multiple channels and markets.
 
 
 In this role, you will drive targeted campaign performance, support business growth, and expand our online reach across both global and regional markets. You will work across platforms such as LinkedIn, Google Ads, programmatic, retargeting, and other relevant media channels, managing audience and geographical targeting while turning campaign data into clear insights and actionable recommendations.
 
 
 
 
 
 We are looking for someone who is analytical, commercially minded, structured, and comfortable working across several brands and stakeholder groups. Familiarity with AI tools for campaign planning, content development, optimisation, reporting, and marketing efficiency will enable you to improve campaign performance and optimise workflows.
 
 
 
 
 
 
 A performance-driven profile with advanced analytical skills
 
 
 
 The ideal candidate has a relevant paid media background and is skilled in managing campaigns from setup to reporting.
 
 
 We also assume that you:
 
 <ul>
 <li>
 Have at least 3 years of experience in paid media, digital marketing, or performance marketing
 </li>
 <li>
 Bring practical experience with LinkedIn Campaign Manager and Google Ads, including Search/Text and Display campaigns
 </li>
 <li>
 Have a deep understanding of audience segmentation, targeting, retargeting, geographical targeting, and campaign optimisation across markets
 </li>
 <li>
 Excel in programmatic advertising, trade media advertising, lead generation, and account-based marketing campaigns
 </li>
 <li>
 Can interpret campaign data and turn it into actionable recommendations with a test-and-learn mindset and close attention to detail
 </li>
 <li>
 You can translate campaign budgets into paid media allocation recommendations, advising Marketing Managers on optimal channel mix and performance impact
 </li>
 <li>
 Have a genuine interest in, or experience using, AI tools to improve marketing workflows and campaign performance
 </li>
 </ul>
 
 
 
 
 
 It is a plus if you have:
 
 
 <ul>
 <li>
 Experience with HubSpot or similar marketing automation/CRM platforms
 </li>
 <li>
 Experience working in B2B marketing, international maritime markets, or industry/trade-focused marketing environments
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 
 At Bunker Holding Group, you will join an international marketing environment where digital performance, innovation, and collaboration are key. You will work with stakeholders across markets and contribute to campaigns that support a global business. We offer comprehensive health insurance and a role with responsibility, room to grow, and the opportunity to directly support how we use paid media, data, and AI-driven tools to improve our marketing activities.
 
 
 
 
 
 
 Apply
 
 
 
 Are you a paid media specialist who thrives on targeting the right audience, optimising campaigns, and turning data into results? Then we would like to hear from you. Please note that applications are handled on an ongoing basis.
 
 
 Submit your application via the Apply button.
 
 
 
 
 
 
 
 Bunker Holding
 
 
 
 is the global leader in purchasing, selling, and supplying marine fuel and lube oil as well as providing risk management and other vital services for the shipping industry. The group operates via more than 1,600 ports worldwide and is present in 32 countries with 62 offices and more than 1,300 skilled employees.
 
 
 
 
 Bunker Holding has a long history but remains forward-looking and focused on answering the needs and challenges of an ever-changing industry. The group is advancing and expanding its efforts in the transition to alternative fuels with an ambition to facilitate the decarbonisation of the shipping industry.
 
 
 
 
 Read more at www.bunker-holding.com
 
 
</div>

Paid Media Specialist

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online in IES (International Emerging Stores - Latam, APAC, MENA and India), this is your chance to make history. 
 
Finance is all about the numbers&hellip;unless you work at Amazon; it&rsquo;s knowing the numbers and so much more. Enthusiasm and energy help us deliver new ideas, and solutions. Do you view problems as treasures, and are you willing to dive deep to develop those solutions and deliver results? Will you seek to challenge the status quo, and accept that your ideas and mechanisms may be tested daily?
 
 
At Amazon, we move with purpose and speed, and this requires we work with a dynamic network of Retail, Operations, Marketing and Tech partners. Our analysts work across teams, help others understand financial decisions and are trusted business advisors. They employ every facet of data and communication to ensure our partners and our leaders have the most up to date and reliable information to help them make the best possible decision. Come teach us a few things, and we&rsquo;ll teach you a few things as we navigate Earth's most customer-centric company! 
 
Key job responsibilities 
<ul><li>Be the go-to FP&amp;A contact for the International Emerging Stores business</li><li>Financial modeling, providing analytical support, and validating financial and operational results of the Consumer business.</li><li>Ensuring a high level of financial controls are followed, maintaining data integrity.</li><li>Lead month-end close activities and planning cycles related to OPEX and headcount.
</li><li>Controllership of IES Stores financials, mainly OPEX, understanding actuals, challenging variances and tracking action plans to bring financial results back to plan when necessary and possible.</li><li>Active business partner driving actuals variances analysis along with other finance teams, such as Payments, Customer Service, Operations, Bad Debts, Prime and Marketing.</li><li>Drive automation and process simplification</li><li>Orchestrating the whole planning process, from aligning assumptions and calendar deliverables to system load and data integrity checks</li><li>Providing accurate and insightful financial reports</li><li>Finding opportunities to use global standards and transfer repetitive tasks to global teams</li><li>Developing financial skills across the organization</li><li>Build great talent inside and outside Finance</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>5+ years of tax, finance or a related analytical field experience</li><li>5+ years of finance experience, or Master&rsquo;s degree and 3+ years of finance experience</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>6+ years of participating in continuous improvement projects in your team to scale and improve controllership with measurable results experience</li><li>6+ years of identifying incomplete or inaccurate data, identifying the root cause and creating/implementing an escalation plan experience</li><li>6+ years of mentoring junior finance and/or business team members experience</li><li>3+ years of working with senior staff (e.g. c-suite) experience</li><li>Experience working with large-scale data mining and reporting tools (i.e. SQL, MSAccess, Essbase or Cognos) and providing recommendations based on results of ad hoc analyses to management for strategic decision-making</li><li>6+ years of applying key financial performance indicators (KPIs) to analyses experience</li><li>MBA, or CPA</li></ul> 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

International Emerging Stores FP&A Finance Manager | Latam, MENA, APAC, India, International Emerging Stores FP&A

Explore 135+ Analytical data scientist in Dubai this July. Find roles across top companies and apply now to boost your career.

135 analytical data scientist jobs In Dubai

Data Scientist II - Analysis, QC

Data Scientist II - Analysis, QC

Data Scientist

Data Scientist Team Lead –

Data Scientist (Arabic Speaker)

Paid Media Specialist

International Emerging Stores FP&A Finance Manager | Latam, MENA, APAC, India, International Emerging Stores FP&A