• Drive the roadmap for customer-facing dashboards and analytics. • Build the value realization story. • Own exportable data feeds and real-time data APIs. • Own the data strategy layer. • Lead data discovery for strategic customer launches. • Partner deeply with Engineering and Data Science. • Manage the trust layer of the data experience.

Role Description We are currently looking for an exceptionally talented Senior Data Scientist to join our team. You will be responsible for: - Extracting insights from complex data sets. - Developing recommender systems. - Applying advanced analytical techniques to drive strategic decision-making and optimize business outcomes. Functional Responsibilities: - Designing models with a user-centric output, such as recommender systems tailored for various applications including offer design, consumer behavior prediction for purchases, and churn prediction. - Conducting exploratory data analysis to uncover hidden patterns and extract valuable insights that contribute to business growth and optimization. - Utilizing predictive modeling and forecasting techniques to support decision-making processes and improve operational efficiency. - Continuously monitoring model performance, assessing data quality, and refining models to ensure accuracy and reliability. - Staying up to date with the latest advancements in data science and technology, and identifying opportunities to apply emerging methodologies to enhance existing models and processes. Qualifications - Minimum of 4 years of professional experience in Data Science, Machine Learning, or a related field. - Strong proficiency in programming languages such as SQL, Python and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning algorithms, statistical models, and data mining techniques. - Proficient in SQL and experience working with databases and data querying. - Problem solver: proactively implements solutions to improve business. - Exceptional communication skills in English (B2-C2), including the ability to convey complex technical concepts, collaborate effectively in team environments, and deliver impactful presentations to diverse audiences. Benefits - Ownership through equity participation. - Annual company retreat. - Education bonus for continuous learning. - Company-wide winter break. - Paid time off. - Optional in-person events and meetups. - Tailored career roadmaps. - High-performance culture.

• Analyzing large sets of data to differentiate legitimate and fraud traffic • Developing and implementing detection rules and models to improve the accuracy and effectiveness of the security products. • Improving processes to collect, manipulate, present, and analyze large datasets in a production-ready environment • Troubleshooting production issues in a very distributed environment

• Analyze Gremlin’s proprietary dataset of millions of chaos engineering experiments to identify failure patterns, root causes, and resilience signals across complex distributed systems • Pretraining and fine-tuning machine learning models that automatically detect, classify, and explain failures observed during chaos experiments • Build intelligent systems that deliver automated remediation recommendations, and eventually orchestration, by learning from historical experiment outcomes and system behavior • Develop scalable data pipelines and feature stores to process, enrich, and serve large volumes of experiment data for both model training and real-time inference • Collaborate closely with platform engineers and SREs to integrate AI-driven failure analysis and remediation capabilities directly into Gremlin’s core product • Apply advanced techniques, including causal inference, graph ML, time-series modeling, and reinforcement learning, to continuously improve the accuracy and actionability of automated failure analysis • Translate insights from millions of chaos experiments into AI-powered features that help customers automatically understand blast radius, pinpoint root causes, and accelerate recovery • Research and productionize novel ML approaches, including causal AI and agentic systems, that turn raw chaos experiment data into automated, reliable remediation strategies