anecdotes is a B-round startup founded in June 2020 that is leading the Compliance Automation space for hyper growth companies. We believe that credible, visible, and actionable data should be the foundation of every GRC (governance, risk, and compliance) team’s decision-making process. That is why we help enterprises collect and standardize data from hundreds of SaaS tools, cloud infrastructures, private networks, databases, and more, to gain continuous visibility into their Security Compliance posture.

We are looking for an experienced Data Scientist/Machine Learning researcher to join my AI R&D team. You will join a team researching and building AI based features with high impact on the product and our customers.

We have:

• Allot of data, both unstructured and structured
• Well defined and feasible research tasks
• Focus on NLP, specifically LLMs
• Experienced leadership
  

What You'll Do:

• Research, POC and finally productize AI based core functionalities
• Work closely with Product and R&D to deliver your algorithms to production
• Produce relevant thought leadership (papers, patents, blogs, conferences, webinars, etc.)
  

Who You Are:

• 5+ years of experience in Data Science/Machine Learning research
• M.Sc. in Computer Science/Mathematics/Physics or any other relevant field (with a Thesis)
• Extensive experience in Python for machine learning - Transformers, Pandas, Sklearn
• Experience in NLP techniques and delivering such components to production
• Used to reading and implementing SOTA techniques based on research papers or open source publications
• A team player and a can-do attitude, delivery oriented
• Curious, creative, and hungry for impact
• Able to quickly learn new tools and data analysis methods
• A self-learner, not afraid to explore new areas of research
• Excellent spoken and written English.

Nice to have:

• Experience with LLMs
• Specific domain expertise - GRC Experience: Prior experience in the Governance, Risk, and Compliance industry is advantageous.
• Experience with designing and training Deep Learning models.
• Familiarity with MLOps tools and working with ML pipelines.
• Experience working in cloud environment (AWS / GCP / Azure)
• High proficiency with SQL

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