Data Scientist

Responsibilities

1. Collaborate with the business intelligence team to utilize historical data in forecasting future trends and detecting fraud.
2. Collaborate with the operations team and the data engineering team to design various systems, which include, but are not limited to:
   1. User activity monitoring and anomaly detection
   2. Content moderation system
   3. Systems for optimization operation workflows
3. Work with the data engineering team to design and implement recommendation systems at scale.

Requirements

1. Fluency in common data science Python libraries, including but not limited to numpy, pandas, scikit-learn.
2. Fluency in several machine learning frameworks, including but not limited to tensorflow / pytorch, keras, theanos, pyspark
3. Proficiency in the basic software development lifecycle and low-level code optimization.
4. A self-directed learning mentality.
5. Comfortable working in an English-speaking environment.

Good to have

1. Knowledge in deep learning based recommender system such as DLRM, Wide & Deep , and NCF.
2. Expertise in building LLM applications and familiarity with foundational models (LLaMA, BERT, GPT, Mixtral 8x7B) and frameworks, such as langchain, weights & biases as well as retrieval mechanisms with vector databases such as pinecone and weaviate.
3. Experience in leading a team and providing mentorship.