Senior Data Scientist

Senior Data Scientist

Location: Fully Remote (USA) PST Time Zone

Job ID: SFDCJP00023978 Contract Length: 03/2025 to 01/30/2026

The enterprise IAM security team is looking for a data scientist to work on AI solutioning for certain IAM products they own. This data scientist will develop, optimize, and test ML models for building IAM solutions with AI. IAM space knowledge is important but not mandatory as the role involves developing and optimizing AI models and working in collaboration with the enterprise security team for gen AI and non gen AI use cases. The candidate should be senior, capable of leading conversations and initiatives on the front, and have previous experience leading a team, driving design conversations, and doing hands on development for ML models.

Skills required:

• Python and ML NLP, RAG, and personalization recommendation systems
• PyTorch and Tensor

Overview of this department and team:

This is a new space for the organization, as they are developing this platform and building it. They don't have anyone doing this on FTE right now. It is a space they are growing and would like to invest in this moving forward. In fact, they will soon have an FTE position, and they will want this contractor to work with them. This is the reason why it's important for the candidate to be self-sufficient, drive things, and have an opinion on the design architecture conversations and managing their own code.

Day to day:

This person will be doing requirements gathering, design, build and deploying of ML models & pipeline. The more experience the better. Mapping the use cases, identity access management systems, etc. As long as they can quickly learn the datasets here and apply to the use cases here, but adopting to their infrastructure and platform will be a part of the job as well.

Interview process:

4 rounds of interviews - 3 technical interviews - can stack them back to back to back. This will be on Python design and development skills, data modeling, prototyping ML models, to assess if they can build multiple seams for building multiple data sets.