Data Scientist
Summary
Own the machine learning models that price used cars for AlgoDriven's automotive appraisal products: design, train and deploy vehicle price forecasting models in Python, integrate them with Node.js services, and apply modern AI techniques (deep learning, time series, LLMs). Hybrid role, 4 days a week in Downtown Cairo.
About AlgoDriven
AlgoDriven builds AI software for the automotive industry. Our products (EvalExpert, DriveExpert and InspectExpert) help dealer groups, banks and OEMs appraise, inspect and price vehicles across Australia, New Zealand, the Middle East and South East Asia.
The role
You'll own the machine learning models that tell our customers what a used car is worth, today and next month. Working mainly in Python in a small team, you'll take models from idea to production and keep pushing their accuracy, including by putting the latest AI developments to work, from modern deep learning and time series architectures to foundation models and LLMs.
Location: Hybrid, 4 days a week in our Downtown Cairo office and 1 day remote. Full-time.
What you'll do
Design, train and deploy machine learning models that predict and forecast vehicle prices
Write clean, production-grade Python for modelling, feature engineering and evaluation
Track new AI research and tooling, and apply the techniques that measurably improve accuracy
Build rigorous validation and backtesting so every improvement is real
Work with market data from websites and APIs, including linking duplicate listings across sources
Integrate models with our Node.js services and monitor them in production
Use SQL to investigate data-quality issues and explain anomalies
Explain results clearly to product, commercial and customer teams
What you'll bring
5+ years as an employed data scientist (not counting internships or study)
Strong Python, including code you've written and maintained in a production ML system
Professional experience building, evaluating and improving machine learning models, including forecasting (prices, demand, sales or similar)
A track record of lifting model accuracy through experimentation, and a habit of keeping up with current AI developments
Experience collecting data from websites and APIs
Professional Node.js experience
Strong SQL
Clear, professional spoken and written English
You enjoy a startup environment with high ownership and few handoffs
Nice to have
Deep learning or LLMs used in production
Experience with automotive, marketplace or pricing data
Our hiring process
Application with short screening questions
A ~25-minute AI-led interview you complete at a time that suits you, reviewed by our team
An online skills assessment (TestGorilla)
A final interview with the hiring manager
Skills
As published by ashby · 11 questions
Basics
Name, Email, Resume
Short answers (1)
- LinkedIn profile URL
Pick from a list (10)
- Can you work from our Downtown Cairo office four days per week?
- How many years have you worked as an employed professional data scientist, excluding internships, education, and personal projects?
- Have you personally written and maintained Python code used in a production data or machine-learning system?
- What is your professional experience with Node.js?
- Have you personally built and evaluated a machine-learning model to forecast numerical values over time, such as prices, demand, or sales?
- Have you built or maintained an automated pipeline that regularly collects data from websites or external APIs?
- Have you used SQL professionally to join multiple tables and investigate data-quality issues?
- We need to predict used-car prices for next month. Which is the best primary test of model performance?
- The same car is advertised on three websites. How should these records be handled?
- Our dataset contains advertised asking prices but no confirmed sale prices. What can we directly train and evaluate a model to estimate?