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We are looking for a Data Analytics Team Lead to help scale our analytics capabilities. This role requires a hands-on leader who will be deeply involved in analyzing data, building classification intelligence, and owning data products and processes. As a Team Lead, you will also work closely with business stakeholders to define KPIs, implement scalable data practices, and mentor a growing team of analysts.

The role is part of the R&D Data team, which is responsible for our data classification capabilities, including blending ML, LLMs, and robust analytics to process millions of files and tables per day.

Responsibilities:
Manage, mentor, and support a team of Data Analysts.
Play a central role in our core mission, working closely with Engineering, Research, Sales, and Customer Success to align priorities and deliver meaningful insights.
Create rules and models to broaden our repertoire of sensitive data classes, from knowledge acquisition to writing production code.
Develop and own robust success metrics for classification performance; monitor, evaluate, and iterate.
Analyze vast datasets spanning multiple organizations, cloud environments, and data technologie.
Create processes and tools that will allow non-technical stakeholders to have a clear view of scanning and classification KPIs.
Make the most of our enormous amounts of data to help drive product and R&D decisions.
Work from within the R&D Data group, take part in the discussions revolving around our data science objectives, priorities and solutions.

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. You should have in-depth knowledge of statistical and data science methodology and tools. Youll join a tight-knit group that values continuous improvement and solving challenging technical and product problems in an emerging space. Plus, we like to have fun along the way.

Responsibilities:
Creating innovative Machine Learning solutions for big data-sparse setups.
End-to-end research and development of scalable Data Science solutions for our use-case challenges.
Maintenance and improvement, if needed, of existing models, including accuracy and performance assessment in production.
Collaborate with Data Engineers to tackle scale-up challenges.