data analytics analyst

AIQU

<div>
 
 We are hiring
 
 Data Analyst
 
 to join one of our major clients based in
 
 Dubai, UAE.
 
 
 
 
 
 
 Job Location - Dubai, UAE
 
 
 Job Type - 12 months Contract (Extendable)
 
 
 
 
 
 
 About Role
 
 
 
 We are seeking a detail-oriented and analytical Data Analyst with experience in Anti-Money Laundering (AML) to support our AML team.
 
 
 
 
 
 
 Required Skills
 
 
 <ul>
 <li>
 3&ndash;8 years of experience as a Data Analyst with AML domains.
 </li>
 <li>
 Strong proficiency in Azure Data Lake- SQL for data extraction, transformation, and analysis.
 </li>
 <li>
 Experience with data visualization and reporting tools such as Power BI.
 </li>
 <li>
 Knowledge of AML, KYC related domains.
 </li>
 <li>
 Bachelor's degree in Data Analytics, Computer Science, Statistics or a related field.
 </li>
 </ul>
 
 
 
 
 
 
</div>

Data Analyst

<div><div>United Arab Emirates Digital &amp; IT 5 - 10 years Dubai On-site
</div>Data Analyst - AML (Arabic) to join one of our Esteemed client in Dubai<div><div> 
<div></div>
</div></div><div><div><div>About The Member Company
We are a global high-tech consultancy company with a team of entrepreneurial engineers, scientists, and digital experts from around the world. Together we form a fast-growing and proud community. We offer consultancy services to high-profile clients globally in diverse service areas, such as:
<ul><li>Technology &amp; Engineering</li>
<li>Energy &amp; Renewables</li>
<li>Life sciences &amp; Pharma</li>
<li>Digital &amp; IT</li>
</ul></div></div></div><div><div><div><div><div><h2 class="jobSectionHeader">About this vacancy</h2>
We are seeking a detail-oriented and analytical Data Analyst with experience in Anti-Money Laundering (AML) to support our AML team.
</div></div></div></div></div><div><div><div><div><div><h2 class="jobSectionHeader">What we expect from you</h2>
Bachelor&rsquo;s degree in data Analytics, Computer Science, Statistics, or a related field.
3&ndash;8 years of experience as a Data Analyst with AML domains.
Strong proficiency in Azure Data Lake- SQL for data extraction, transformation, and analysis.
Experience with data visualization and reporting tools such as Power BI.
Knowledge of AML, KYC related domains.
</div></div></div></div></div><div><div><div><div><div><h2 class="jobSectionHeader">What you can expect from us</h2>
TMC is an international high-tech consultancy company that brings expertise to its clients in order to support them with the realization of their technological challenges. As such, TMC is operating as an expert center at the disposition of its clients and we help them to be more competitive in an ever more global and faster-changing technological world. At TMC we believe that people are the driving force behind technological innovation. That is why we want to create the best possible conditions for tech talents to thrive in. We offer you a challenging and stimulating work environment in which you can be the director of your own career. As an Employeneur you are part of our TMC family. Next to our outstanding technical expertise, fun and engagement are meaningful parts of our culture.</div></div></div></div></div></div>

Data Analyst - AML (Arabic)

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>

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

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

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.
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Refineries Analyst

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