About the Role
Lead end-to-end deployment of advanced analytics pipeline, collaborating with product managers, data engineering, or backend engineer team
Translating business needs to data science problems, and performing experiments to validate the hypothesis
Develop machine learning models (ML)/advanced analytics algorithms using state-of-the-art methods
Design analytics framework (ML and statistical model) for various use cases
Maintain the quality and execution of the analytics models for various products
Perform periodic review on the implementation of the model and data pipeline
Collaborate with analytics team to advice on the usage of Hypefast data asset to solve business problems
Perform exploratory data analysis on various data sources to get new insights to improve and give recommendation for new product development or online experimentation
Discuss and align with stakeholders on key product metrics, design and propose experimentation strategies
Launch A/B tests, analyze experiment results and provide recommendations
Requirements
Have 2+ years of experience in ML/DL
Bachelor's Degree in Mathematics, Statistics, Computer Science, or Data Analytics.
Strong command in python, SQL, etc.
Proficient in developing ML pipelines using Cloud Run, Airflow, Vertex AI GCP is a plus
Having experience in a Recommendation System is a plus
Strong academic background in concepts of machine learning and deep learning (DL)
Hands-on experience in working with deep learning frameworks like tensorflow, pytorch, etc.
Comfortable deploying code in cloud environments/on premise environments
Be comfortable and flexible in working in an environment where priorities evolve
Write clean code has the habit of maintaining a clean documented code
Understand best practices in ML/DL and is continuously open to learning