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.

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.

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.
• Experimentation and causal thinking: Design, analyze, and interpret A/B tests. Partner with product and engineering to ensure correct tracking and experiment quality.
• Modeling for decisions (practical ML): Build baseline predictive and segmentation models with clear evaluation and limitations.
• Applied AI (LLMs) for analytics and decisioning: Prototype small, safe LLM use cases. Help define evaluation and validation approaches.
• Analytics that ships: Create reusable, well-documented analysis assets and collaborate with data engineering to productionize reliable pipelines.
• Data quality and reliability: Validate data inputs, monitor key metrics, and investigate anomalies.
• Responsible use of AI tools: Use AI to accelerate work while validating outputs and protecting sensitive data.

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, statistics fundamentals, and basic modeling.
• 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.
• Familiarity with modern analytics stacks (dbt, BigQuery, Snowflake, Looker, PowerBI, Tableau).
• Exposure to ML tooling (scikit-learn, notebooks, basic MLOps concepts) and version control (Git).
• Familiarity with LLM concepts through coursework or side projects.
• Understanding of product analytics concepts and causal pitfalls.
• Experience creating AI-ready data assets.
• 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 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.