About Us

Tamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.

Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.

Your Role

We are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.

You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.

Your Responsibilities

Model Deployment & Scaling

• Productionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architectures
• Design low-latency, high-availability APIs and pipelines for real-time model inference.
• Implement batch scoring systems for periodic risk assessments.=

MLOps & Infrastructure

• Build and maintain CI/CD pipelines for model deployment and monitoring.
• Set up automated feature engineering pipelines, leveraging feature stores.
• Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.

Model Monitoring & Maintenance

• Implement real-time and batch monitoring for data drift, concept drift, and model performance.
• Build automated retraining workflows and model rollback mechanisms.

Collaboration with Risk DS

• Work closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.
• Advise DS on efficient model architectures for operational environments.
• Optimize feature computation for speed and scalability.

System Design & Integration

• Integrate models with credit underwriting, fraud detection, collections, and merchant risk systems.
• Collaborate with backend engineering to align on API contracts and system interfaces.

Your Expertise

• 6+ years of experience as an MLE, ML Engineer, Mlops Developer.
• Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).
• Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).
• Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).
• Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).
• Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).
• Proven track record of deploying and maintaining ML models in production at scale.
• Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).

All qualified individuals are encouraged to apply.

The Role:

Ziina is looking for a Senior Data Platform Engineer to join our team. This role is an exciting opportunity to build the foundations of our data platform from the ground up — the pipelines, warehouse, and tooling that will power decision-making, analytics, and future ML/AI capabilities across the company. We're at a major inflection point in our growth, and we're looking for the right person to shape how data is ingested, modeled, and consumed at Ziina as we scale.

As part of a small, agile team, our ideal candidate is a creative problem-solver with the vision to build from the ground up and the skill to own systems end-to-end. You'll thrive in our fast-paced environment by making sound tradeoffs and focusing on high-impact solutions. We're looking for someone who is as ambitious as we are to deliver high-quality products to our users. In short, we want owners who are ready to build big things with us.

As a Senior Data Platform Engineer at Ziina you will:

• Build and maintain scalable data pipelines and processing systems that ingest data from transactional databases, object storage, and external APIs
• Design and evolve our data warehouse architecture and data models to support analytics, reporting, and ML/AI use cases
• Improve the reliability, observability, and performance of our data systems
• Implement data quality checks and monitoring to ensure trusted, accurate data across the company
• Enable self-service data access and analytics so product, engineering, and business teams can make data-driven decisions independently
• Support the foundational capabilities that will power our ML and AI use cases as they grow

To succeed in this role, you likely:

• Bring 5+ years of experience in Data Engineering, Data Platform, or Analytics Engineering
• Have strong expertise building and maintaining data pipelines with orchestration tools like Dagster, Airflow, or Prefect, and writing ETL/ELT workflows in Python
• Are proficient with modern data warehouses (Snowflake, BigQuery, or Redshift) and transformation frameworks like dbt
• Have hands-on experience ingesting data from a mix of sources — PostgreSQL, S3, external APIs — supporting both transactional and event-driven use cases
• Are familiar with data quality, observability, and monitoring practices for production data systems
• Use the latest AI tools and technologies to boost your productivity
• Are based in, or open to relocating to, the UAE

What would amaze us

• Proven experience building data platforms at fintech or other high-scale, high-reliability companies
• A track record of designing data warehouse architectures and models that scaled cleanly as the company grew
• History of building self-service analytics tooling that meaningfully expanded who in the company could work with data
• Experience enabling ML/AI workloads on top of a data platform — feature stores, ML pipelines, or serving infrastructure
• Active engagement in the data community through open source contributions, conference speaking, or technical writing

Our tech stack:

The data platform is a core investment area at Ziina. Our current stack is:

• Snowflake as our data warehouse, with dbt for data transformation and modeling
• Dagster for orchestrating data pipelines, with Python for building ETL/ELT workflows
• Data ingestion from PostgreSQL, S3, and external APIs, supporting both transactional and event-driven use cases
• Metabase for analytics and internal reporting

The broader Ziina engineering stack that the data platform integrates with:

• Typescript, Node.js and Nest.js for our main application's backend
• GraphQL Federation for our client-facing APIs and Kafka for our inter-service communication
• PostgresSQL for consistent and durable storage, Redis for quick fetching, Elasticsearch for quick searching
• AWS for hosting our cloud infrastructure and Kubernetes for orchestrating our workloads
• Terraform for IaC, GitHub Actions for CI/CD

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We’re backed by Accel, Lightspeed, NfX and other top-tier investors.

Role Overview

We are seeking a talented Analytics Lead to build and lead our analytics function from the ground up. This role is crucial for establishing our core data infrastructure and delivering actionable insights across all teams to power strategic decision-making and drive business growth.

Key Responsibilities:

• Data Infrastructure & Governance:
  
  
• Design and implement our core analytics infrastructure, including data warehousing, ETL processes, and visualization tools.
• Establish data quality standards, automate routine reporting, and create self-service analytics tools to ensure data accuracy and accessibility.

• Business Intelligence & Insights:
  
  
• Create and maintain dashboards for key business metrics across operations, finance, partnerships, and growth teams.
• Develop comprehensive analytics for transaction monitoring, liquidity optimization, platform performance, and revenue forecasting.
• Analyze user behavior and transaction patterns to drive growth strategies.

• Risk & Financial Analytics:
  
  
• Build analytics models for pricing optimization and financial planning.
• Create risk monitoring systems and fraud detection analytics to ensure platform security.

• Strategic Partnership & Team Leadership:
  
  
• Partner with leadership to provide data-driven insights for strategic decision-making.
• Build, manage, and mentor a high-performing team of analysts as the organization scales.

What we are looking for

Must-haves:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
• 6+ years of experience in analytics or data science roles.
• Strong programming skills in Python and SQL.
• Experience with modern data stack tools (e.g., Snowflake, dbt, Airflow).
• Proven experience building and maintaining large-scale data pipelines.
• Excellent communication skills with the ability to present complex data to non-technical stakeholders.
• Strong problem-solving skills and meticulous attention to detail.

What helps you stand out:

• A Master's degree in a relevant field.
• Experience in a fintech or financial services environment.
• Direct experience with crypto/blockchain analytics.
• Startup experience is highly preferred.
• Expertise with data visualization tools like Tableau or Looker.

What We Offer

• Competitive salary and benefits package.
• Equity in a rapidly growing company.
• Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
• Opportunity to make a significant impact on global financial infrastructure
• Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. 

Employment Type: Full-time & Permanent

Location: Dubai, UAE (Visa sponsorship and relocation assistance provided) 

Annual Base Salary range of $80,000 - $110,000 per annum + performance-based bonus - 0% tax environment + opportunity to join our employee share scheme

About Cobblestone Energy

Cobblestone Energy is an energy trading company specialising in the European Gas, Power and Emissions markets. Established in 2018, we combine deep analytics, advanced data science and agile technology to drive profitable trading decisions. Our flat organisational structure empowers every team member with autonomy and ownership. Our diverse global team of extraordinary talent is united by a relentless pursuit of excellence.

Cobblestone Values

• Excellence in Hiring & Teamwork
• Lifelong Learning Through Continuous Reflection
• Independent Thinking Through a Meritocracy of Ideas
• Winning

Role Description:

We are seeking a highly motivated and talented Data Scientist to join our dynamic team. With a passion for data-driven solutions and a strong academic background, the successful candidate will play a critical role in shaping business decisions and driving operational excellence through advanced analytics, predictive modelling, and the strategic implementation of Generative AI/LLM technologies.

What we offer in this role 

• A full-time, high-impact position within our dynamic Commercial team.
• A team of exceptional colleagues, committed to continuous learning and pushing the boundaries of what’s possible.
• A career that challenges you to solve complex problems and rewards your drive for continuous innovation.
• A unique opportunity to work on impactful projects, making independent decisions that drive real-world outcomes.
• The chance to take full ownership of new projects, making high-impact decisions in a dynamic environment.
• Equity participation, ensuring long-term alignment

Key Responsibilities: 

• Analyse large, complex datasets to generate actionable insights that inform trading and commercial decisions.
• Develop, deploy, and maintain predictive models to support market forecasting and trading strategy optimisation (e.g., time-series models, regression, tree-based methods).
• Architect and implement production-ready AI/LLM solutions, such as Retrieval-Augmented Generation (RAG) pipelines or task-specific agents, integrated programmatically into analytical workflows (e.g., via APIs, LangChain, LlamaIndex).
• Build, automate, and own end-to-end data workflows covering data ingestion, cleaning, feature generation, and model training, leveraging tools such as Python, SQL, Airflow, pandas, and workflow orchestration platforms (e.g., n8n or similar).
• Apply advanced data science techniques, including synthetic data generation where appropriate, to improve model robustness, scalability, and operational efficiency.
• Collaborate closely with traders and cross-functional stakeholders to translate business problems into high-quality, data-driven solutions.
• Communicate insights and model outputs clearly and concisely, ensuring analytical work drives measurable trading and commercial impact.

Requirements: 

• 2-3 years of experience in data science or a related field, with a demonstrated record of achieving exceptional results.
• Strong academic background in computer science, mathematics, statistics, or a related field 
• Outstanding problem-solving and critical thinking skills, capable of addressing complex, high-impact challenges.
• Expertise in Python programming, with an ability to apply it to advanced data science problems.
• Applied AI Proficiency: Demonstrated practical experience programmatically integrating LLMs (via APIs or frameworks like LangChain/LlamaIndex) into data pipelines or analytical applications.
• Automation Focus: Proven ability to design and implement automated, end-to-end data workflows that leverage AI for efficiency gains.
• Knowledge of machine learning algorithms and data visualization tools 
• Exceptional communication and collaboration skills, with a demonstrated ability to excel in fast-paced, cross-functional environments

This is an outstanding opportunity for a driven and talented Data Scientist to join an innovative trading company and make a significant impact on our business operations. If you possess a passion for data science and a proven track record of success, we encourage you to apply. 

Note: Experience in the power trading domain is highly desirable but not essential. We value exceptional talent and the ability to learn quickly.