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Lokker is a platform that helps organizations understand and control how data is collected and shared across their digital properties. The company continuously analyzes websites, applications, third-party technologies, and data flows to identify privacy, security, and consent risks in production, leveraging a large proprietary dataset built from years of observing real-world digital behavior.
As a Data Scientist, you will develop and improve machine learning models that classify digital activity, identify meaningful privacy and security behaviors, and assess the confidence and significance of findings. Your work will directly impact the product and be used by privacy teams, engineers, lawyers, and insurers—so explainability and accuracy are equally important.
Key responsibilities include: developing and improving production classification models; building features and signals from large-scale behavioral and network data; improving training data, labeling, evaluation, and model quality; developing confidence and risk-scoring approaches that support product decisions; producing explainable outputs that help users understand findings; and building evaluation, regression, and monitoring systems to maintain model quality over time. You'll also explore new approaches for identifying emerging privacy and security risks.
This is primarily a structured-data machine learning problem with opportunities to use LLMs and other techniques where they add meaningful value. You will work closely with engineering, product, and privacy experts.
Required qualifications: 2–4 years of production experience in data science, machine learning, or data engineering; strong Python and SQL; experience with pandas or Polars, scikit-learn, and modern classification techniques; solid grounding in supervised learning with ability to frame classification problems, choose appropriate metrics, and design production-grade validation; rigorous evaluation skills to identify overfitting and slice-level failures; practical experience using LLMs beyond simple demonstrations; familiarity with containerization and cloud services; and curiosity about how websites, applications, and internet technologies behave.
Bonus experience includes privacy, advertising technology, web analytics, entity resolution, anomaly detection, cloud data platforms, browser automation, or large-scale web data. No privacy or adtech background required—the company will teach the domain.
