Causal Inference Data Scientist - Recommendation System (Startup)

Company Description

Puritype is an idea-sharing platform that aims to promote free and open discussions without censorship. Our goal is to accelerate the development of recommender systems to enhance daily life experiences. We believe in the power of technology and innovation to connect individuals and provide personalized recommendations.

Role Description

This job is going to build MVP (minimum viable product). The Data scientist will be responsible for developing causal inferences methods to estimate the effect of treatment and implementing machine learning algorithms, pattern recognition. They will also work on data analysis, statistical modeling, and algorithm optimization. The Machine Learning Engineer will collaborate with a team of engineers and data scientists to improve recommender systems.

As a Machine Learning Engineer, you will work with Data Scientist in causal inference to build recommendation system, where an end-to-end AI system processes raw sensor input to make direct decisions, we are building end-to-end AI based recommendation algorithms. These algorithms aim to discover the most compelling content on platform including posts, promoted content, creators, and videos based directly on users activity on the platform. As a key driver of this effort, you will test state-of-the-art methodologies to significantly enhance users experiences on the platform.

Your responsibilities will include:

Designing and architecting recommendation algorithms across various product surfaces (Timelines, Video, Search, Notifications)

Collaborating with cross-functional teams to integrate machine learning models into our platform

Iterating and improving the algorithm by gathering user feedback in real time through experimentation

Ensuring scalability and efficiency of machine learning systems

Mentoring junior engineers and contributing to the team's growth

Staying updated on Machine Learning and Deep Learning industry trends

Qualifications

Strong background in Computer Science and Statistics

Experience in developing and implementing machine learning algorithms

Knowledge of pattern recognition and Causal inference

Proficiency in programming languages such as Python or R

Familiarity with algorithms and data structures

Strong analytical and problem-solving skills

Excellent communication and collaboration abilities

Master's or Ph.D. in Computer Science, Engineering, or related field

Experience with recommender systems is a plus