Data Scientist, Doodle

AI Systems

Salary not provided

Python

Junior, Mid and Senior level

Berlin

More information about location

Office located in Kohlfurter Str, Berlin

Online scheduling and meeting software

Be an early applicant

Online scheduling and meeting software

101-200 employees

B2BInternal toolsProductivitySaaS

Be an early applicant

Salary not provided

Python

Junior, Mid and Senior level

Berlin

More information about location

Office located in Kohlfurter Str, Berlin

101-200 employees

B2BInternal toolsProductivitySaaS

Company mission

To make scheduling as simple as possible.

Job

Company

Role

Who you are

You're more than an analyst; you're a builder, a problem-solver, and a continuous learner who thrives on applying AI to real-world impact
If you're excited by the intricacies of machine learning pipelines, the power of generative AI, and the precision required when working with human time and behavior, you'll find a stimulating environment here
You're a practical AI builder who thinks in terms of customer value
You have experience designing and evaluating models and are proficient in Python
You understand model behavior and output evaluation
You are familiar with RAG, Graph-based retrieval, prompt design, and multi-hop reasoning
You're comfortable with the full lifecycle of an AI component, from planning and modeling to testing and continuous improvement

What the job involves

At Doodle, we're building the future of scheduling and productivity, tackling complex challenges at the intersection of human collaboration and digital efficiency. We believe in crafting elegant solutions to intricate problems, and we're looking for passionate Data Scientists who share this drive
You'll shape and refine our core AI systems, playing a pivotal role in designing and training models that are accurate, scalable, and resilient
You will be the architect of our intelligent systems, from a data and modeling perspective. You will design, explore, and prototype solutions for complex problems
Explore and implement Retrieval-Augmented Generation (RAG) or Graph RAG approaches to improve the quality of information retrieval and reasoning in LLM workflows. This includes graph construction, entity linking, and hybrid scoring strategies
Contribute to prompt design and continuously evaluate prompt results to ensure model outputs are reliable and aligned with user goals
Design and implement solutions using various neural network architectures beyond LLMs, such as Convolutional Neural Networks (CNNs) for image tasks or Recurrent Neural Networks (RNNs) for sequential data, based on the specific problem
Develop evaluation frameworks for testing model output quality, reliability, and alignment with user goals (e.g., hallucination detection, prompt regression, safety scoring)
Contribute to our AI strategy and roadmap, helping shape how we scale the use of models responsibly across the platform. This includes thinking beyond LLMs to select the right neural network architecture for a given task
Prototype and evaluate AI features on platforms like Claude or Amazon Bedrock, with a focus on production readiness
Quantize large models into smaller, more efficient models to enable edge intelligence and on-device processing

Application process

We usually respond within two weeks
Initial Application Review
Personality & Strengths Assessment (via BRYQ)
Home Assignment
Technical Interview
Meet the Team/Hiring Manager
Culture Fit Conversation
Final Offer & Next Steps

Our take

In recent years, creating an accessible and smooth remote working system has become a requisite for many companies. One company focused on this is Doodle, an online scheduling and meeting platform.

Boasting 30M monthly users across 70,000+ businesses, a huge sell is the software can be used for teams of all sizes. This means its features are accessible to small independent businesses through to large enterprises. As a result, the company has placed itself at the forefront of the market (competing with the likes of Calendly).