We are seeking a highly motivated quantitative researcher to join our Investment Management & Research group, focussing on MENA Equities. You will play a key role in researching, developing and operating our equities strategies in the region, partnering with portfolio managers, researchers, and technology to build and optimise the full strategy lifecycle – from research and back testing to live trading and risk management.

You will spend an initial period of approximately 6 months working in our London office before relocating to our office in Abu Dhabi.

Your responsibilities will include:

• Conduct in-depth research to identify alpha-generating strategies in MENA equity markets
• Research and back test systematic trading signals
• Collaborate closely with portfolio managers, researchers and technologists to develop trading infrastructure and strategies
• Monitor, analyse and report on strategy performance

What we are looking for: 

• 3+ years of experience working in a systematic equity trading environment
• Proficiency in data analysis and programming, preferably using Python and key libraries such as Pandas and NumPy
• Exceptional understanding of signal research and portfolio construction
• Strong communication skills with the ability to work in a distributed and collaborative research environment.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Why Tamara?

We’re proud to be Saudi’s first FinTech unicorn.
Our mission is to help people own their dreams by building the most customer-centric financial super app in the world. & There is no playbook for that; our Tamarians are writing it. Our teams are made up of innovators, problem-solvers, and learners we thrive on curiosity and collaboration.
If this sounds like you: curious, driven, and ready to build, we’d love to meet you
Apply now and join the next generation of Builders!

About the Program: 

At Tamara, we believe exceptional talent deserves an exceptional launchpad.

Our Flagship Builders Program is designed for ambitious graduates ready to step into real responsibility from day one. This isn’t a rotational “observer” program, it’s a career accelerator built for those who want to build, own, and raise the bar early.
Designed for recent graduates and early-career talent with up to two years of experience, the program places you directly into high-impact roles across Product, Engineering, Design, and beyond. You’ll contribute immediately and grow at an accelerated pace.
From Product to Engineering, Design to Commercial, you’ll tackle meaningful challenges that shape how millions experience fintech across the region. You’ll be trusted with ownership, surrounded by high-caliber peers, and mentored by leaders who expect excellence.

Our January and June cohorts are your opportunity to move fast, think big, and start building what’s next - not someday, but now.

About the role:

We're looking for a fresh graduate or early-career Data Analyst on an analytical engineering path.

This role blends the best of data analysis and data engineering. You will help turn raw data into trustworthy, well-modeled datasets that:

• make definitions consistent (so "the number" means the same thing everywhere)
• improve data quality and reliability
• enable self-serve analytics and AI-assisted insights across teams (not just dashboards)

You will also help make Tamara’s data AI-ready by building well-defined datasets, metrics, and documentation that can be safely used by AI tools (and people) across the company.

With the advancement of AI, we value people who have strong fundamentals and clear thinking. Understanding data structures, measurement, tradeoffs, and how to validate results matters more than memorizing tools. You'll learn how to use AI responsibly to move faster, while still owning correctness, data quality, and interpretation.

You will collaborate with a diverse ecosystem of engineers, product experts, and business to solve real problems that impact our customers and business outcomes.

Your responsibilities

• Model and transform data for analysis
  • Build and maintain clean, reusable datasets (fact and dimension tables) that power reporting and self-serve analytics.
  • Contribute to a scalable metrics layer: define, document, and align business definitions (for example, "active user", "approval rate", "default rate").
• Support analytics and decision making
  • Answer ad-hoc questions with clear analysis and explainable methodology.
  • Turn common questions into reusable, self-serve assets: dashboards and AI-enabled workflows (a curated dataset + definitions that an AI assistant can query correctly, plus validated example analyses).
  • Create AI-friendly data products (well-defined datasets, metrics, and documentation) that teams can query through AI tools.
• Enable AI-ready analytics
  • Package datasets and metrics so they can be reliably used by AI tools (clear grain, business definitions, data contracts, examples).
  • Write AI-friendly documentation: glossary, metric definitions, common queries, and pitfalls.
  • Partner with AI and platform teams to ensure critical tables are discoverable, permissioned correctly, and safe to use.
• Ensure data quality and reliability
  • Write basic tests, checks, and monitoring for key datasets and critical metrics.
  • Troubleshoot data issues and improve reliability from source to reporting.
• Work effectively with engineering and product
  • Collaborate with data engineers on schema changes, event tracking, and pipeline improvements.
  • Translate ambiguous business questions into measurable analyses, and communicate findings clearly.
• Use AI tools thoughtfully
  • Use AI to accelerate SQL drafting, code scaffolding, and documentation.
  • Validate AI outputs, document assumptions, and protect sensitive data.

Your expertise (must have)

• Fresh graduate or < 1 year of relevant experience (internships, projects, or part-time roles count).
• Solid SQL fundamentals (joins, aggregations, basic window functions).
• One programming language for analysis (preferably Python) with basic skills in:
  • Data manipulation (tables/dataframes)
  • Basic statistics (distributions, sampling intuition, confidence basics)
• Strong analytical thinking:
  • Ability to define a problem, form hypotheses, validate data, and explain results.
• Strong attention to detail and commitment to accurate, reliable outputs.
• Ability to work effectively in a team-oriented environment.

Nice to have

• Exposure to data modeling concepts (star schema, slowly changing dimensions, metrics definition).
• Familiarity with modern analytics stacks (dbt, BigQuery, Snowflake, Looker, PowerBI, Tableau) through coursework or projects.
• Experience creating AI-ready data assets (clean semantic layers, metric definitions, data contracts, documentation, and evaluation or sanity-check checklists) is a plus.
• Experience using AI assistants responsibly to accelerate analysis or analytics engineering work (for example, SQL drafting, code scaffolding, documentation).
• Experience with version control (Git) or basic software engineering practices.
• Understanding of event tracking and product analytics (funnels, cohorts, retention).
• Knowledge of responsible data handling (PII basics, access controls, safe sharing).

What success looks like

• You can independently produce a well-structured analysis with clear assumptions and validation steps.
• You contribute at least one reliable dataset or transformation that becomes a shared building block for analytics.
• Stakeholders can answer more questions with self-serve and AI-assisted exploration, with less back-and-forth.
• A key dataset or metric you built becomes usable through AI tools with consistent answers (validated against a source-of-truth definition).
• You can spot when results look off, debug quickly, and explain the root cause.

Why Tamara?

We’re proud to be Saudi’s first FinTech unicorn.

Our mission is to help people own their dreams by building the most customer-centric financial super app in the world. & There is no playbook for that; our Tamarians are writing it. Our teams are made up of innovators, problem-solvers, and learners we thrive on curiosity and collaboration.

If this sounds like you: curious, driven, and ready to build, we’d love to meet you

Apply now and join the next generation of Builders!

About Tamara's Builders Program 

At Tamara, we believe exceptional talent deserves an exceptional launchpad.

Our Flagship Builders Program is designed for ambitious graduates ready to step into real responsibility from day one. This isn’t a rotational “observer” program, it’s a career accelerator built for those who want to build, own, and raise the bar early.
Designed for recent graduates and early-career talent with up to two years of experience, the program places you directly into high-impact roles across Product, Engineering, Design, and beyond. You’ll contribute immediately and grow at an accelerated pace.
From Product to Engineering, Design to Commercial, you’ll tackle meaningful challenges that shape how millions experience fintech across the region. You’ll be trusted with ownership, surrounded by high-caliber peers, and mentored by leaders who expect excellence.

Our January and June cohorts are your opportunity to move fast, think big, and start building what’s next - not someday, but now.

About the role

We’re looking for a fresh graduate or early-career Associate Data Scientist on a builder path.

This role blends product thinking, applied statistics, and production-minded analytics. You will:

• turn ambiguous problems into measurable questions
• build reliable measurement (metrics and experimentation)
• create lightweight models and decision tools that teams can use in real workflows
• partner closely with engineering, product, and risk to improve customer outcomes and business performance
• build AI-assisted decision workflows (for example, LLM-powered analysis copilots backed by a curated metrics layer, with clear guardrails and validation)

With the advancement of AI, we value people who have strong fundamentals and clear thinking. Understanding data generation, measurement, tradeoffs, and how to validate results matters more than memorizing tools. You'll learn how to use AI responsibly to move faster, while still owning correctness, robustness, and interpretation.

Your responsibilities

• Define problems and measurement
  • Translate product or business questions into testable hypotheses and clear success metrics.
  • Build and maintain metric definitions and analysis templates so decisions are consistent and repeatable.
• Experimentation and causal thinking
  • Design, analyze, and interpret A/B tests (and quasi-experiments when randomization is not possible).
  • Partner with product and engineering to ensure correct tracking, guardrails, and experiment quality.
• Modeling for decisions (practical ML)
  • Build baseline predictive and segmentation models (for example, churn propensity, risk signals, customer clustering) with clear evaluation and limitations.
  • Focus on models that are actionable: who will use them, when, and what decision they change.
• Applied AI (LLMs) for analytics and decisioning
  • Prototype small, safe LLM use cases that improve how teams explore data (for example, natural-language Q&A over a curated dataset, summarizing experiment results, or generating investigation checklists).
  • Help define evaluation and validation approaches for AI-assisted outputs (sanity checks, golden queries, offline test sets, and human review loops).
  • Partner with platform and security stakeholders to ensure AI workflows are permissioned correctly and avoid leaking sensitive data.
• Analytics that ships
  • Create reusable, well-documented analysis assets: datasets, feature tables, notebooks, dashboards, and simple services or jobs.
  • Collaborate with data engineering to productionize reliable pipelines where needed.
• Data quality and reliability
  • Validate data inputs, monitor key metrics, and investigate anomalies.
  • Document assumptions and build sanity checks so analyses and models are trustworthy.
• Responsible use of AI tools
  • Use AI to accelerate coding, documentation, and exploration.
  • Validate AI outputs, protect sensitive data, and follow safe data handling practices.

Your expertise (must have)

• Fresh graduate or < 1 year of relevant experience (internships, capstone projects, or part-time roles count).
• Strong SQL fundamentals (joins, aggregations, window functions).
• One programming language for data (preferably Python) with basic skills in:
  • Data manipulation (tables/dataframes)
  • Statistics fundamentals (distributions, sampling intuition, confidence basics)
  • Basic modeling (regression/classification basics and evaluation intuition)
• Strong analytical thinking:
  • Ability to define a problem, validate data, and explain results clearly.
• Strong attention to detail and commitment to accurate, reliable outputs.
• Ability to work effectively in a team-oriented environment.

Nice to have

• Exposure to experimentation platforms or frameworks (for example Statsig, Optimizely, internal experimentation tooling).
• Familiarity with modern analytics stacks (dbt, BigQuery, Snowflake, Looker, PowerBI, Tableau) through coursework or projects.
• Exposure to ML tooling (scikit-learn, notebooks, basic MLOps concepts) and version control (Git).
• Familiarity with LLM concepts (prompting basics, retrieval/RAG intuition, and evaluation approaches) through coursework or side projects.
• Understanding of product analytics concepts (funnels, cohorts, retention) and causal pitfalls (selection bias, confounding).
• Experience creating AI-ready data assets (clean semantic layers, metric definitions, data contracts, documentation, and sanity-check checklists).
• Knowledge of responsible data handling (PII basics, access controls, safe sharing).

What success looks like

• You can independently deliver an end-to-end analysis with clear assumptions, validation steps, and a concrete recommendation.
• You help ship at least one decision tool (experiment, metric framework, or lightweight model) that changes a product or business decision.
• Stakeholders can run repeatable analyses with less back-and-forth, and your work reduces ambiguity in key metrics.
• You can spot when results look off, debug quickly, and explain the root cause.

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.

About Us:
Founded 20 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people operating throughout North America, Europe and Asia. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users. Now, DV group affiliates include two broker dealers, a cryptocurrency market making firm, and a bourgeoning investment adviser.

DV Commodities is a division within DV Group that specializes in trading commodities markets, including crude oil, refined products, natural gas, power, emissions, metals, softs, and agriculture. DV Commodities risk management, world-class technology, and talented traders have enabled it to become one of the world’s largest liquidity providers and risk allocators in the energy and commodities spaces. Learn more here.

Responsibilities:

• Primary owner of P&L in one or multiple areas of energy business
• Build and maintain fundamental and quantitative trading models
• Work with risk to ensure compliance with agreed upon risk management metrics and sizing
• Liase side by side with senior energy traders to share best practices / learnings where applicable
• Learn proprietary methodologies and trading systems that support an established trading business
• Grow existing trades and P&L while identifying and pursue new opportunities
• Further responsibilities may be driven by the individual’s interests and specific skills

Requirements:

• Energy trading experience required
• Self-starter with entrepreneurial spirit
• Able to learn quickly in a fast paced, high pressure environment
• Targeted ISO experience and knowledge of fundamental grid
• Detail oriented, organized, diligent
• Maintain composure and communicate clearly when under pressure
• Ability to succeed working as part of a diversified team
• Strong understanding of math, probability, and statistics
• High level of proficiency in Excel and VBA; SQL, python, statistical modeling, other programming a plus
• Advanced aptitude for problem solving and multitasking
• Proven track record with historical P&L preferred

DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DV’s posted positions. All resumes submitted by search firms to DV via e-mail, the Internet, personal delivery, facsimile, or any other method without a valid written agreement shall be deemed the sole property of DV, and no fee will be paid in the event the candidate is hired by DV. DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.

We are looking for a Senior Quantum Field Engineer. As a Senior Quantum Field Engineer, you’ll be part of a team whose mission is to lead IonQ on its journey to build the world’s best quantum solutions and solve the world’s most complex problems.  Field Engineering sits at the intersection of customers, markets, products and product teams, algorithms, applications, innovation and strategy - this is the team where ideas become applied and have impact.

Join a nimble team of scientists, engineers, salespeople, marketers, business developers, and product managers to drive an entirely new quantum computing business. We’re seeking versatile engineers and architects skilled in technical sales, technical demos and customer interactions who feel energized to deliver IonQ’s quantum computing products and quantum applications. 

Responsibilities:

• Inspire prospective clients by explaining IonQ’s strategy, portfolio and answering technical questions about quantum portfolio (compute, network, security, sensing and space) and quantum applications.
• Lead and shepherd client discussions, inspiring them to see how quantum applications can be implemented in their business domain.
• This includes working through business needs and mapping Quantum Algorithms (financial services, bioscience, chemistry and materials, optimization, generative AI, and other domains) into application code and executing Proof-of-Concepts together with the IonQ Application team.
• Share insights from clients with the IonQ Product Management and Engineering teams such that client feedback is incorporated into our products.
• Navigate competitive objection handling
• Translate business needs expressed by our clients into technical work projects in collaboration with other team members.
• Create assets to explain features of our quantum applications and other IonQ quantum products.
• Move dialogs from initial ideation to focused exploration domain through to proof-of-concept and ultimately into production workflows.
• Lead client discovery sessions for business oriented use cases that uncover potential overlap with development of useful quantum algorithms together with the IonQ Application team
• Partner with marketing, developer relations and business development to grow awareness of IonQ in the world at large.
• Attend industry conferences, as needed, to talk to client and support our booth activities.
• Some travel expected in the US (20%) but opportunities for global travel are available as well for client meeting and IonQ conference activities.
• This is a technical customer-facing role with the appropriate balance of compensation acceleration for success and a base salary to ensure that credibility and technical correctness always comes first.

You’d be a good fit with:

• 5 years of experience in technical customer-facing roles or equivalent capacity.  The ability to communicate (at the various context-appropriate levels of depth) and persuade clearly, have strong EQ, and other customer facings skills are critical.
• Bachelor’s degree or above in Computer Science, Machine Learning, Data Science, or other STEM field, such as Chemistry, Physics or Engineering
• Motivated learner with a strong interest in quantum computing.

You’d be a great fit with: 

• Masters or PhD in a STEM field, perhaps adjacent to quantum computing.
• Time on the customer side in various verticals included leadership roles - this provides customer empathy
• Hands-on experience with Qiskit, Cirq or other quantum computing SDK.
• Proficient in Python and Jupyter Notebooks.
• Expert architecture skills across various technologies (“full stack skills”)
• Experience leading technical events.

Location: This role is based in Saudi Arabia or Dubai, UAE, and requires candidates to be locally based in one of these locations.
Travel: 20% travel domestically and globally
Job ID: 1374

The Role

We are seeking an exceptionally talented individual to join our Cross-Asset Derivatives Risk Management team as a Risk Manager. This role will focus on risk management and portfolio oversight of the firm’s Equity Derivatives, Macro EM and Delta One strategies, which include Equity vol, Fixed Income, Index Rebalance & Special situations strategies amongst others.

What you’ll do 

As a Risk Manager, you will:

• Report to the Head of Cross-Asset Derivatives Risk and partner daily with Portfolio Managers, Strats, and developers to monitor portfolios and design solutions that reduce concentration and stress risks.
• Build, implement and validate models that power both risk management and the investment process.
• Partner with our Technology organisation to enhance data infrastructure, automate risk-limit monitoring and streamline raw-data ingestion.
• Work with Portfolio Managers, providing regular and ad-hoc analytics on strategy performance, risk profiles and tail-risk scenarios.
• Collaborate with strategy COO, fellow risk managers and tech teams to build and maintain the modelling, pricing and analytics toolkit that powers our multi-strategy platform.

What you’ll bring
What you need:

• A minimum of 5 years’ relevant experience in a PM-facing role
• Strong knowledge of equity derivatives and portfolio risk management
• Knowledge of quantitative finance including risk-neutral options pricing and cross-sectional factor models
• Experience analyzing and modeling large data sets
• Strong coding skills in one or more languages such as R, Python or C++
• Experience working with relational databases such as MySQL
• Strong communication skills

We’d love if you had:

• Direct experience in Macro, Delta one and Equity Derivatives Strategy

Who we are

Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.

Our Culture

At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.

#LI-DK1

The role of a Data Scientist at Dataiku is quite unique. Our Data Scientists not only code up solutions to real-world problems, but also participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, some user training, and co-developing data science projects from design to deployment.

Just as non-technical skills are important, so too are technical skills. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team primarily uses Python and SQL, with occasional work in other languages (e.g., R, PySpark, JavaScript). An ideal candidate is excited to learn complex new technologies and modelling techniques while being able to explain their work to other data scientists and clients.

In this role, you'll help the team:

• Co-develop production-level data science projects with our customers

• Analyse and investigate various kinds of data and machine learning applications across industries and use cases

• Help users discover and master the Dataiku platform, via user trainings, office hours, and ongoing consultative support

• Provide data science expertise both to customers and internally to Dataiku’s sales and marketing teams

• Develop custom Python-based “plugins” in collaboration with Solutions, R&D, and Product teams, to enhance Dataiku’s functionality

You might be a good fit for the role if you have:

• English - fluent, Arabics - fluent/native will be a big plus

• Curiosity and a desire to learn new topics and skills

• Empathy for others and an eagerness to share your knowledge and expertise with your colleagues, Dataiku’s customers, and the general public

• The ability to clearly explain complex topics to technical as well as non-technical audiences

• 2 - 10 years of experience with Python and SQL

• 2 - 10 years of experience with building ML models and using ML tools (e.g., sklearn)

• Familiarity with data visualisation in Python and R

• Understanding of underlying data systems such as Cloud architectures, Hadoop, or SQL

Technical skills that may help you in the role:

• Experience with Consulting and/or Customer-facing Data Science roles

• Experience with Data Engineering or MLOps

• Experience developing WebApps in JavaScript, RShiny, or Dash

• Experience building APIs

• Experience using enterprise data science tools

• Passion for teaching or public speaking

#LI-AS2

Available Locations: Dubai

What you’ll do

The Pre-Sales Solutions Engineering organisation is responsible for the technical sale of the Cloudflare solution portfolio for the Digital Native Business, ensuring maximal business value, fit-for-purpose solution design and efficient adoption roadmaps for our customers. Solution Engineering is made up of individuals from a wide range of backgrounds - from Financial Consulting to Product Management, Customer Support to Software Engineering, and we are serious about building a diverse, curious and collaborative team.

As a Solutions Engineer, you are the technical customer advocate within Cloudflare. You will aid your customers and will work closely with every team at Cloudflare, from Sales and Product to Engineering and Customer Support to do so. Your goal of customer success should drive you through the entire organisation as you seek out and create scalable solutions for your customer’s needs.

The range of products and solutions offered by Cloudflare are broad so that we are able to meet our lofty goal of helping to build a better Internet. A broad knowledge of Internet performance and security technology is required, the curiosity to maintain and develop new knowledge is essential to keeping up with the high rate of product innovation at Cloudflare. 

All the resources and training required to be effective for the role, will be provided. 

Examples of desirable skills, knowledge and experience

Our Solutions Engineers come from a wide range of backgrounds: IT, engineering, software development, product management, financial consulting, customer support & project delivery. We're serious about building a diverse team. When hiring we look for diversity of experience combined with genuine curiosity for our technology.

Ultimately, you are passionate about technology and have the ability to explain complex technical concepts in easy-to-understand terms. You are naturally curious, and an avid builder who is not afraid to get your hands dirty. You appreciate the diversity of challenges in working with customers, and look forward to helping them realise the full promise of Cloudflare. On the Solutions Engineering team, you will find a collaborative environment where everyone brings different strengths and jumps in to help each other.

You will have a good fundamental understanding on how to obtain the technical win so that customers choose our proposed solutions over that of competitors.

Additional experience might include a combination of the skills below:

• 3-to-10 years of experience in the IT industry (early or mid-level experience).
• Fluent English (written & spoken)
• experience with Oracle, AWS, MS or leading cybersecurity solution
• Ability to manage a project, work to deadlines, and prioritise between competing demands.
• Demonstrating empathy with customers and quickly identifying challenges and pain points they face. 
• Understanding of “how the internet works”. For example:
  • Know the differences between TCP & UDP, and understand what kinds of applications may favour one over the other;
  • Can explain the difference between authoritative DNS & recursive DNS?;
  • You understand the role of a firewall, why TLS (SSL) plays an increasingly important role on today's Internet, a solid understanding of HTTP and a willingness to dive deeper into the quirks of clients & servers alike;
• Understanding of how customers make buying decisions, how to explain ROI.
• A knowledge of the competitive landscape for one or more of: DDoS, CDN, Performance, DNS, Developer platform or Zero-Trust/SASE service providers.
• You're OK with some travel (10-15 days per quarter): we expect to travel to customer offices, conferences and/or do talks.

Bonus!

• Previous experience in a pre-sales SE or consulting role. (note: doesn't have to be in tech);
• Demonstrated experience with a scripting language (e.g. Python, JavaScript, Bash) and a desire to expand those skills;
• Exposure to emerging technical landscape trends in Security such as Zero Trust.

• Tip of the Spear: Lead the deployment of WorkOS in the field. You will be responsible for understanding a customer's operational "chaos" and architecting an AI-driven solution that fixes it in weeks, not months.
• Rapid-Fire Execution: Build, iterate, and ship. You will write high-quality, full-stack code to create bespoke integrations and augment our platform’s core capabilities and create custom agents. This goes beyond context engineering; you’ll build the connective tissue - integrating bespoke APIs, setting up RAGs and Evals, tuning the E2E system and performance, and architecting multi-agent handoffs.
• Feedback Loop Mastery: You are the eyes and ears of the product team. You will translate field-tested insights into core product requirements, ensuring WorkOS remains grounded in real-world utility.
• Winning Stakeholders: Act as the technical face of WorkOS. You’ll need to win the trust of stakeholders, navigate complex enterprise hierarchies, and persuade skeptics by shipping results that speak for themselves.
• Technical Versatility: One day you’re setting up a RAG pipeline; the next, you’re debugging a legacy enterprise API or designing a custom dashboard. You do whatever is necessary to make the solution land.

• 5–8+ years of high-octane engineering experience. You are likely a senior-level engineer who is "hungrier" than your peers and bored by traditional, slow-moving dev cycles.
• The FDE Pedigree: Experience in forward-deployed, mission-driven environments (e.g., Palantir, high-growth startups, or specialized consultancy) where you worked directly with customers.
• Full-Stack Polyglot: Mastery of the modern stack (React/TS, Python/Node) with the ability to jump into any codebase and be productive on day one.
• AI Fluidity: Strong working knowledge of LLMs, prompt engineering, and agentic frameworks. You don't just know the theory; you know how to make AI work in production.
• Excellent Communication: You are a "social engineer." You can explain complex AI logic to a CEO and then pivot to a deep-dive session with an infrastructure lead without missing a beat.
• Relentless Bias for Action: You are a builder who values shipping over perfection. You have a "founder-level" sense of ownership and aren't afraid to get your hands dirty.
• Willingness to work on-site full time in UAE, with occasional travel to be embedded with regional partners.

• A Blank Canvas and Live Ammunition: The rare opportunity to build a "0-to-1" product while immediately deploying it into the real-world operations of a regional giant. No "sandbox" projects here, you’ll be shipping code that moves people and goods on day one. This is a huge opportunity to create impact in our region.
• A Special Ops Mission: We’re a lean, impact-obsessed team operating with total autonomy. You’ll be free from corporate bureaucracy and legacy baggage, focused entirely on winning the customer and solving "unsolvable" problems.
• Direct Collaboration with Leadership: Direct engagement with Careem and enterprise client leadership, in addition to working side-by-side with the WorkOS founding team including Magnus Olsson (Careem’s original Co-founder).

About the team

The Careem Data Science team’s mission is to drive competitive value from data at scale through building AI models to optimize user experiences, decision-making, operational efficiencies, and lead the region’s AI ecosystem. As one of the tech leaders in this team, you will be at the forefront of fulfilling this mission. You will be working with the top data science talent of the region, while innovating on our user experience using GenAI.

What you'll do

• Be part of a 0-1 AI transformation for the Careem app from a personalization perspective.
• Build a long-term vision on how we can rethink our customer acquisition and engagement strategies, leveraging data in our decision-making.
• Drive exploratory analysis to understand the ecosystem, user behavior, and identify new levers to help move metrics and build models of user behaviors for analysis and product enhancements.
• Shape and influence data/ML models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products.
• Provide product leadership by sharing data-based recommendations to communicate the state of the business, the root cause of change in metrics, and experimentation results, influencing product and business decisions
• Implement scalable machine learning algorithms that will be used in production on big data.
• Embark on exploratory data analysis projects to achieve a better understanding of phenomena as well as to discover untapped areas of growth and optimization. 
• Answer complex analytic questions from big data sets to help Careem shape its products and services in a better way.
• Help define and track the appropriate key metrics for specific projects. 
• Design and run randomized controlled experiments, analyze the resulting data, and communicate results with other teams.
• You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices.
• Build and deploy retrieval augmented generation systems and other applications of large language models.

What you'll need

• 7-9 years of experience in data mining, predictive modeling, time series analysis, machine learning, Big Data methodologies, and transformation and cleaning of both structured and unstructured data.
• Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.
• Solid experience with Deep Learning Techniques (e.g, attention, retrieval models, etc)
• 1-2 years of industrial experience in personalization, recommendation or search is a MUST. Preferably working in a product-driven company.
• Strong problem-solving and coding skills.
• Solid knowledge of AB testing, classic ML, and DL
• Solid understanding of recommendations, ranking, and retrieval. 
• Proficiency and demonstrated experience in: Python, SQL, Spark, Hive.
• Demonstrated experience with database technologies (e.g. , Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).
• Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik) along with geospatial data processing skill, is a plus.

About the Role

We’re looking for senior technical leaders who can architect and scale intelligent systems that architect the "brain" of our dark store operations. As a senior data scientist you won’t just be building models, you’ll be optimizing the lifecycle of millions of items from the moment they leave a supplier to the moment they reach a customer’s doorstep in under 20 minutes. You will tackle the classic "perishable trade-off" ensuring our shelves are always stocked with what customers want, while ruthlessly minimizing wastage and maximizing every square centimetre of our dark store floor space.

What You'll Do

• Demand Forecasting: Build and deploy high-precision forecasting models to predict hyper-local demand at the SKU-store level.
• Inventory & Availability: Develop replenishment algorithms that balance In-Stock Availability with the risk of expiry, specifically for high-turnover perishables.
• Wastage Mitigation: Use ML to identify items at risk of expiring and trigger automated interventions including reduced-to-clear discounting, intra-store replenishment etc.
• Dynamic Pricing & Discounts: Design and A/B test pricing strategies that move inventory efficiently without eroding margins.
• Space Management: Optimize dark store space determining which items should be stored where within the dark store to minimize picker travel time and maximize storage density.
• End-to-End Ownership: Work closely with Product Managers and Supply Chain Operations to turn your models into production-level code that dictates real-world logistics.

What You'll Need

• Academic Background & Experience: 8+ years of experience in Data Science, ideally in E-commerce, Q-commerce, or Supply Chain. A background in Operations Research or Statistics. Hands-on proficiency in Python, Spark and ML frameworks. Experience with real-time inference systems and model monitoring in production. Strong understanding of experimentation, A/B testing, and causal inference. Demonstrated ability to drive architectural decisions across teams.
• Technical Skills: Professional-grade Python and SQL. Experience with optimization libraries (like Gurobi, CPLEX, or PuLP) and ML frameworks (XGBoost, LightGBM, or PyTorch).
• Problem Solving: Experience with Stochastic Optimization or Reinforcement Learning for inventory management is highly preferred.
• Business Intuition: You understand that a 1% reduction in wastage across 100+ stores translates to millions in saved EBITDA.
• Communication Skills: Excellent communication skills and ability to translate complex modelling trade-offs into business impact.

What We’ll Provide You

We offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:

• Work and learn from great minds by joining a community of inspiring colleagues.
• Put your passion to work in a purposeful organisation dedicated to creating impact in a region with a lot of untapped potential.
• Explore new opportunities to learn and grow every day.
• Work 4 days a week in office & 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year. (If you are in an individual contributor role in tech, you will have 2 office days a week and 3 to work from home.)
• Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.

About the Role

As a Staff Data Scientist I – ETA, you will own the end-to-end ETA prediction systems for Careem’s Food and Groceries verticals. This is a highly technical Individual Contributor role with full domain ownership across architecture, modeling strategy, experimentation, production deployment, and operational excellence.

You will define the long-term vision for ETA systems in high-load, latency-sensitive marketplace environments. You will design and implement multi-stage stochastic pipelines that model preparation time, assignment delay, pickup time, travel time, batching, and pooling effects delivering reliable, calibrated predictions at scale. This role requires deep expertise in time-series forecasting, deep learning, and operations research combined with strong production experience in distributed and real-time systems. You will collaborate closely with Product, Engineering, Marketplace, and Operations leaders, ensuring ETA becomes a core competitive advantage in Careem’s Everything App.

What You'll Do

1. ETA Vision & Architecture Ownership

• Define and own the long-term technical vision for ETA systems across Food and Groceries.
• Architect scalable, multi-stage pipelines.
• Design probabilistic and stochastic modeling approaches with uncertainty calibration and reliability guarantees.
• Establish modeling standards and best practices for ETA across the organization.

2. Advanced Modeling & Algorithm Development

• Develop and deploy production-grade ML systems leveraging:
• Deep learning architectures
• Time-series forecasting
• Graph-based and routing-aware models
• Operations research techniques
• Build models robust to marketplace volatility and supply-demand shifts.
• Optimize for both point accuracy and distributional correctness (confidence intervals, tail control).
• Continuously improve system performance under high traffic and low-latency constraints.

3. Production Systems & Real-Time Inference

• Design and deploy scalable real-time inference pipelines.
• Ensure model reliability, monitoring, alerting, and graceful degradation under load.
• Collaborate with Data Platform and ML Ops teams to productionize models using Spark, Trino, Python, and distributed frameworks.
• Lead model lifecycle management, retraining strategies, and performance tracking in live environments.

4. Experimentation & Marketplace Impact

• Define clear evaluation frameworks aligned with business metrics (conversion, cancellations, fulfillment efficiency, customer trust).
• Design and run controlled experiments to measure ETA improvements and marketplace impact.
• Drive measurable improvements in operational efficiency and user experience through data-driven insights.

5. Technical Leadership & Cross-Team Influence

• Lead cross-team architectural discussions.
• Conduct design reviews and raise the technical bar for modeling quality and system robustness.
• Mentor senior data scientists and engineers in advanced ML and modeling techniques.
• Contribute to Careem’s applied AI community through technical talks, documentation, and research initiatives.
  
  

What You'll Need

• 8+ years of experience in Applied Machine Learning or Data Science, with significant experience building large-scale production systems.
• Advanced degree in Computer Science, Statistics, Engineering, Operations Research, or a related quantitative field.
• Proven expertise in:
• Time-series forecasting
• Deep learning
• Stochastic modeling
• Operations research and optimization
• Strong experience building and deploying high-load, low-latency ML systems.
• Hands-on proficiency in Python, Spark and ML frameworks.
• Experience with real-time inference systems and model monitoring in production.
• Strong understanding of experimentation, A/B testing, and causal inference.
• Demonstrated ability to drive architectural decisions across teams.
• Excellent communication skills and ability to translate complex modeling trade-offs into business impact.
  
  

What we’ll provide you

We offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:

• Work and learn from great minds by joining a community of inspiring colleagues.
• Put your passion to work in a purposeful organisation dedicated to creating impact in a region with a lot of untapped potential.
• Explore new opportunities to learn and grow every day.
• Work 4 days a week in office & 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year. (If you are in an individual contributor role in tech, you will have 2 office days a week and 3 to work from home.)
• Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.

About the Role

As a Staff Data Scientist I – Matching, you will own the end-to-end matching and dispatch architecture for Careem’s Food and Groceries verticals. You will design and implement real-time assignment systems that optimize cost, SLA compliance, and marketplace efficiency at scale.

This role sits at the core of the marketplace engine solving complex, multi-objective optimization problems under uncertainty. You will build systems that dynamically match orders to captains, optimize batching and pooling decisions, and continuously re-optimize as new information arrives. You will operate as a senior technical IC, leading architecture decisions, mentoring other data scientists, and setting optimization standards across the domain.

What You'll Do

1. Matching & Dispatch Architecture Ownership

• Design and own the end-to-end matching and dispatch systems for Food & Groceries.
• Architect scalable assignment frameworks incorporating:
• Static and dynamic assignment
• Online matching under uncertainty
• Batch and pooling optimization
• Continuous re-optimization with dynamic events
• Establish robust optimization standards and best practices across the organization.

2. Multi-Objective Optimization & Algorithm Development

• Formulate and implement multi-objective optimization models balancing:
• Cost minimization
• SLA compliance
• Marketplace efficiency
• Develop and deploy:
• Min-cost flow and assignment models
• Graph-based optimization frameworks
• Custom solvers and OR-Tools based solutions
• Incorporate stochastic elements and uncertainty-aware decision-making into assignment policies.
• Continuously refine matching quality under high-scale marketplace conditions.

3. Real-Time Systems & Production Delivery

• Build production-grade real-time matching systems using Python, Spark, and Trino.
• Design scalable pipelines capable of handling large-scale, high-throughput marketplace events.
• Collaborate with Engineering and Platform teams to ensure reliable model serving and system performance.
• Lead performance monitoring, diagnostics, and system optimization.

4. Experimentation & Impact Measurement

• Define evaluation metrics aligned with marketplace and operational objectives.
• Design and run controlled experiments to quantify matching improvements.
• Analyze system trade-offs and communicate clear, data-driven recommendations to Product and Operations stakeholders.
• Ensure decisions translate into measurable improvements in efficiency and SLA performance.

What You'll Need

• 6–8+ years of experience in Applied Machine Learning, Optimization, or Data Science.
• Advanced degree in Computer Science, Engineering, Operations Research, Mathematics, or a related quantitative field.
• Strong expertise in:
• Optimization and assignment algorithms
• Graph modeling and min-cost flow problems
• Multi-objective optimization
• Dynamic and online decision systems
• Hands-on experience with OR-Tools or custom optimization solvers.
• Proficiency in Python, SQL, Spark, and distributed data systems.
• Experience building real-time or near-real-time decision systems.
• Strong understanding of experimentation and performance evaluation in marketplace systems.
• Excellent communication skills with the ability to explain algorithmic trade-offs in business terms.

What we’ll provide you

We offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:

• Work and learn from great minds by joining a community of inspiring colleagues.
• Put your passion to work in a purposeful organisation dedicated to creating impact in a region with a lot of untapped potential.
• Explore new opportunities to learn and grow every day.
• Work 4 days a week in office & 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year. (If you are in an individual contributor role in tech, you will have 2 office days a week and 3 to work from home.)
• Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.

The Mission
We believe the transformative potential of AI is significantly under-realised in our region. To bridge this gap, we are incubating a new division within Careem dedicated to Enterprise AI Transformation. 
We are reimagining and building the future of work to simplify and improve how businesses function in the era of GenAI with WorkOS: a next-generation ‘operating system’ designed to deploy, orchestrate, and improve AI agents across every customer and operational journey (and increasingly autonomously). This isn’t just automation; it’s about creating a hybrid workforce where self-learning AI agents handle the heavy lifting, empowering our people to focus on the highest-value, most creative work.

The Team
This group operates as a startup within Careem with a distinct mandate: move fast, build boldly, and deliver production-grade AI systems that fundamentally change how the region leverages technology. 

The Opportunity
We are looking for an exceptional founding Backend Engineer to build the WorkOS platform. This is a role for a systems-thinker who wants to work at the intersection of high-scale distributed systems and AI orchestration. You will be responsible for building the "brain" of WorkOS, the engine that deploys and manages autonomous agents across the region’s most complex operational journeys at massive scale.

As one of the first engineers in WorkOS, you will have a disproportionate impact on our technical foundation, culture, and the speed at which we move from 0 to 1.

What You’ll Do

• Architect and Build the WorkOS Engine: Design and build the scalable backend services and architectures required to orchestrate complex AI workflows and real-time data streaming. Leverage novel technologies to build cutting-edge capabilities. 
• Set the Engineering Gold Standard: As a founding member, you will establish our backend best practices, from CI/CD and observability to security and system integrity, ensuring a high-velocity but rigorous engineering culture.
• Solve for Distributed Complexity: Navigate the unique challenges of integrating AI agents into legacy enterprise stacks, ensuring low-latency communication and robust data consistency.
• Database design: Build our data infrastructure, leveraging relational, schemaless, and vector stores to power the platform and create persistent brains for our Agents. 
• Full-Cycle Ownership: Own the lifecycle of the platform, from rapid prototyping of new agent capabilities to maintaining production-grade systems at enterprise scale.
• Drive AI-Accelerated Engineering: Constantly experiment with AI-assisted development to move faster than traditional teams, while maintaining a bar for superb technical quality and craft.
• Lead Pioneer Deployments: While building the core platform, you will occasionally lead the charge on first-of-their-kind implementations for strategic partners, ensuring our tech solves real-world operational complexity.
• Operate with High Agency: In this lean, startup-style environment, you will be responsible for outcomes over inputs, rolling your sleeves up to code and balancing investments in the long-term technical roadmap with the need to ship value quickly.

What You’ll Need: 

• 8–12+ years of professional backend engineering experience, with significant tenure acting as a Staff Engineer or Technical Lead for complex, high-scale distributed systems.
• Mastery of Backend Systems: Deep expertise in languages like Python, Go, or Node.js, with a proven track record of architecting concurrency, microservices, and high-throughput data pipelines.
• AI-Native Infrastructure Depth: Hands-on experience with LLM orchestration (LangChain, etc.), vector databases (Pinecone, Milvus), and RAG architectures at a production-grade level.
• Systems-Level Visionary: The ability to design "platform-first", thinking in terms of APIs, modularity, and extensibility so that the WorkOS core can support infinite customer use cases.
• Obsession with Performance: A specialist's focus on latency and system observability; you believe that AI interactions must feel "instant" and "bulletproof" to be valuable.
• Startup-level Autonomy: Comfortable navigating a "0-to-1" environment where you define the technical roadmap and ship high-quality code without a playbook.
• Willingness to work on-site full time in UAE, to foster the high-intensity collaboration required for this incubation phase.
• Experience with enterprise software transformation or legacy system integration is a significant plus.

What You’ll Receive:

• A Blank Canvas and Live Ammunition: The rare opportunity to build a "0-to-1" product while immediately deploying it into the real-world operations of a regional giant. No "sandbox" projects here, you’ll be shipping code that moves people and goods on day one. This is a huge opportunity to create impact in our region. 
• Architecting the Engine: We’re a lean, impact-obsessed team operating with total autonomy. You’ll be free from corporate bureaucracy and legacy baggage, focused entirely on building the core orchestration layer and agentic frameworks that will serve as the "brain" of the region’s enterprises.
• Direct Collaboration with Leadership: Direct engagement with Careem and enterprise client leadership, in addition to working side-by-side with the WorkOS founding team including Magnus Olsson (Careem’s original Co-founder). 
• Competitive Compensation: Including direct equity in this new division. Our philosophy is meritocratic: we want you to own a meaningful stake in the value you create.