Simple
Simple is a successful mobile product that has a user base of over 15 million people and has over 100% year-over-year revenue growth. It helps people improve their nutritional habits through personalized programs, meal tracking, and health insights, which allows them to lead healthier and happier lives.Now, we are taking the next big step and working on a new revolutionary AI product that helps each person improve their health in a fun and engaging way.
Right now we are looking for a highly technically skilled Data Scientist to join the DS Team. This awesome one is expected to take the project and independently bring the model to the production: from discussing the task with the business owners and to monitoring the quality of the data and results of the AB.Data Science team covers all areas of ML for the business: you need to work a lot with tabular data, text and LLM, time series and recommendation systems. In the near future there will be a lot of tasks for research and coming up with solutions specific to nutritionology.
What you’ll do:
Apply modern data science techniques for solving business problems;
Challenge existing models to ensure the best performance;
Ensure understanding of our model behavior in production;
Work with LLM: write prompts, functions, fine-tune if needed;
Create services and monitoring pipelines with the help from DevOps team;
Collaborate with development, analytics and other business teams to understand needs and requirements.
What we look for:
3+ years of experience in Data Science;
Strong proficiency in machine learning algorithms;
Specialization in at least one of ML areas (Recommendation systems; Tabular data and “product” ML: LTV, dynamic pricing; NLP; CV, time-series, RL);
Strong understanding of ML System Design;
Substantial experience with Python, main ML libraries, SQL, Git, Docker;
Strong problem-solving abilities, a keen eye for details and unparalleled commitment to deliver high-quality work;
Result driven and impact oriented.
It will be a strong plus:
Experience with compression methods for NN;
Exposure to MLOps;
Appreciation of software engineering best practices.
Our tech stack:Snowflake (DWH)
Kuberflow + Neptune (models training)
Arize (monitoring)
Docker + FastAPI for streaming
Perks and benefits:
Competitive salary package commensurate with experience, plus stock options;
In-office, hybrid work and remote opportunities;
Relocation package (Cyprus);
The equipment you need to do your job;
A premium SIMPLE subscription;
21 days annual leave, plus bank holidays (those observed where you live);
Support to learn English, should you need (or want) to;
Flexible hours. We focus on your results, not how long you spend at your desk.
To apply for this job please visit boards.greenhouse.io.