Tamara
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.
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Associate Data Scientist - Builders Program - (Emirati National)
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.
Ready to apply?
Apply to Tamara
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 Machine Learning Engineer on a builder track.
This role is for someone who wants to take ML from “cool idea” to “running in production”. You will work across data, modeling, and software engineering to build, deploy, and operate models that improve customer experience, reduce risk, and unlock operational efficiency.
With the advancement of AI, we care more about fundamentals than buzzwords. Use AI assistants to move faster, but always own correctness, safety, privacy, and performance.
Your responsibilities
- Build and ship ML systems
- Develop and deploy ML models and services that solve real business problems.
- Write production-quality code, tests, and documentation.
- Own the full model lifecycle
- Help with data understanding, feature creation, training, evaluation, and iteration.
- Set up offline and online evaluation, and monitor performance after release.
- Make ML reliable in production
- Improve model serving reliability, latency, and cost.
- Implement monitoring for data drift, model drift, and key quality metrics.
- Participate in incident response and postmortems when needed.
- Work with data and platform teams
- Partner with data engineers and platform engineers on pipelines, event-driven signals, and data quality.
- Use event streaming patterns when appropriate (near-real-time features, online scoring, CDC signals).
- Build tools that help others move faster
- Contribute to reusable training and serving components (templates, libraries, CI/CD, feature pipelines).
- Help enable safe self-serve ML and AI usage across teams.
- Use AI tools thoughtfully
- Use AI to accelerate prototyping, debugging, documentation, and test generation.
- Validate outputs, document assumptions, and protect sensitive data.
Your expertise (must have)
- Fresh graduate or < 1 year of relevant experience (internships and projects count).
- Solid programming fundamentals in Python (preferred) or another language used for ML systems.
- Strong fundamentals in:
- Data structures and algorithms (enough to write efficient, reliable code)
- Probability and statistics basics
- ML fundamentals (supervised learning, overfitting, validation, metrics)
- Comfort working with data using SQL and/or Python.
- A problem-solving mindset and curiosity to learn quickly.
- Clear communication and a collaborative approach.
Nice to have
- Experience with common ML libraries (scikit-learn, PyTorch, TensorFlow) through coursework or projects.
- Familiarity with model deployment patterns (APIs, batch scoring, streaming/online scoring).
- Exposure to MLOps concepts (experiment tracking, model registry, CI/CD, monitoring).
- Familiarity with cloud (GCP/AWS) and containers (Docker) is a plus.
- Understanding of responsible AI and privacy (PII handling, access control, evaluation).
- Experience using AI assistants responsibly for coding and analysis.
What success looks like
- You ship at least one end-to-end ML improvement (model, feature, or service) that runs reliably.
- You can explain model performance clearly: what improved, what did not, and why.
- Monitoring is in place for your models, and you react quickly when metrics drift.
- You reduce manual effort for the team by adding a reusable component, template, or automation.
Ready to apply?
Apply to Tamara
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 Platform Engineer on a builder track.
This role is for someone who wants to build the foundations behind analytics and AI. You will help develop and run the data platform that makes data available, secure, governed, and fast. That includes pipelines, event streaming ingestion, warehouses and lakes, and the guardrails that keep data trusted.
With the advancement of AI, we care more about strong fundamentals than memorizing tools. Use AI assistants to move faster, but always own correctness, reliability, and security.
Your responsibilities
- Build and maintain the data platform
- Help develop and maintain platform architecture (data warehouse, data lake, governance, protection).
- Keep the platform reliable, observable, and ready to scale.
- Build robust pipelines (ELT/ETL + event-driven)
- Build the infrastructure required for optimal extraction, transformation, and loading using SQL and big data technologies.
- Augment batch pipelines with event-driven patterns where it makes sense (streaming ingestion, CDC, near-real-time processing, and reliable delivery).
- Improve pipeline performance, cost, and reliability.
- Make the platform easier every week
- Identify, design, and implement internal improvements: automate manual processes, optimize data delivery, and redesign components for scalability.
- Enable analytics and AI use cases
- Build platform primitives and data products that power self-serve analytics and AI-assisted insights (not only dashboards).
- Support analytics tooling that uses the pipelines to deliver actionable insights into customer acquisition, operational efficiency, and key business metrics.
- Partner with stakeholders
- Work with stakeholders including Executive, Product, Data, and Design teams to resolve data technical issues and support infrastructure needs.
- Keep data secure across boundaries
- Help keep data separated and secure across national boundaries, including through multiple data centers and appropriate access controls.
Your expertise (must have)
- Fresh graduate or < 1 year of relevant experience (internships and projects count).
- Solid programming fundamentals in Python, Java, Go, or similar.
- Strong SQL fundamentals.
- Understanding of data concepts: schemas, partitions, data quality, SLAs, and basic security/PII awareness.
- A problem-solving mindset and comfort debugging systems end-to-end.
- Clear communication and a collaborative approach.
Nice to have
- Familiarity with cloud data stack concepts (warehouses, object storage, orchestration, streaming).
- Exposure to event streaming (Kafka concepts like topics, partitions, consumer groups) or CDC.
- Experience with dbt, Airflow, Spark, or similar tools (coursework or projects count).
- Basic Terraform/IaC and CI/CD familiarity.
- Experience using AI assistants responsibly for coding, debugging, and documentation.
What success looks like
- You ship at least one production-ready pipeline or platform improvement that reduces toil or improves reliability.
- You can debug a data issue from source to downstream consumption with clear root cause and fix.
- Teams can onboard to data sources faster, with better documentation and fewer manual steps.
- Platform reliability and data quality improve in measurable ways (latency, failures, freshness, or coverage).
Ready to apply?
Apply to Tamara
Associate Data Analyst - Builders Program - (Emirati National)
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.
Ready to apply?
Apply to Tamara
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 AI Engineer on a builder track.
This role sits between software engineering and applied AI. You will build AI-powered features end-to-end: from turning a product problem into an AI approach, to building pipelines and evaluation, to shipping reliable services in production.
You’ll work with both classical ML and generative AI (LLMs, RAG, agents) where they make sense. With the rapid pace of AI, we care more about fundamentals than buzzwords. Use AI assistants to move faster, but always own correctness, privacy, safety, and user impact.
Your responsibilities
- Build AI products that ship
- Design and implement AI-powered features and internal tools.
- Integrate models into real systems (APIs, workflows, dashboards, and operational processes).
- Work with LLMs in a production-ready way
- Build retrieval-augmented generation (RAG) pipelines: data sourcing, chunking, embeddings, retrieval, and prompt templates.
- Build agent-style workflows when needed (tool use, guardrails, and deterministic fallbacks).
- Own evaluation and quality
- Define what “good” means: success metrics, offline tests, and human-in-the-loop review.
- Set up evaluations for quality, safety, latency, and cost.
- Make AI reliable and safe
- Add observability: logging, tracing, and monitoring for quality regressions.
- Implement privacy and security controls (PII handling, access control, redaction where needed).
- Participate in incident response and postmortems when AI systems misbehave.
- Partner across teams
- Work with product, data, design, and engineering stakeholders to translate messy problems into measurable solutions.
- Collaborate with platform teams to use existing data pipelines, event streams, and AI tooling responsibly.
- Use AI tools thoughtfully
- Use AI assistants for prototyping, debugging, and documentation.
- Validate outputs, document assumptions, and protect sensitive data.
Your expertise (must have)
- Fresh graduate or < 1 year of relevant experience (internships and projects count).
- Solid programming fundamentals in Python (preferred) or another language used for backend services.
- Strong foundations in:
- Software engineering basics (APIs, testing, reliability)
- Data handling (SQL and/or dataframes)
- ML/AI fundamentals (training vs. inference, evaluation, overfitting intuition)
- Clear communication and a collaborative approach.
Nice to have
- Hands-on experience with LLMs and/or RAG from projects (LangChain/LlamaIndex or similar patterns).
- Familiarity with model serving and deployment (REST/gRPC services, batch jobs, streaming consumers).
- Exposure to MLOps concepts (experiment tracking, model registry, monitoring).
- Familiarity with vector databases, search, or information retrieval.
- Understanding of responsible AI, privacy, and security (PII handling, access control, prompt injection awareness).
- Experience using AI assistants responsibly for coding and analysis.
What success looks like
- You ship at least one AI feature or internal tool that is used by real users.
- You set up a simple evaluation and monitoring loop so the system improves over time.
- Your solutions balance quality, latency, and cost, with clear tradeoffs.
- When the AI output is wrong or risky, you can debug, mitigate, and explain why.
All qualified individuals are encouraged to apply.
Ready to apply?
Apply to Tamara