Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
Job Description
We are seeking a Data Scientist to develop next-generation Security Analytics products. You will work closely with engineers and product managers to prototype, design, develop, and optimize data-driven security solutions.
As a Data Scientist, you will focus on consolidating and analyzing diverse data sources to extract meaningful insights that drive product innovation and process optimization. The ideal candidate has a strong background in quantitative analysis, machine learning, and data-driven decision-making, with experience handling large datasets.
Responsibilities:
Conduct exploratory data analysis (EDA) and apply statistical methods to extract actionable insights from complex datasets.
Collaborate with Product Management and cross-functional stakeholders to define problem statements, develop solution strategies, and design scalable ML systems.
Design, develop, and deploy Machine Learning models, including traditional ML, Deep Learning, and Large Language Models (LLMs), to drive business impact.
Create insightful data visualizations, technical reports, and presentations to communicate findings to technical and non-technical audiences.
Deploy ML models in production and implement monitoring frameworks to ensure model performance, stability, and continuous improvement.
Requirements:
2-5 years of experience in Machine Learning projects, including model development, deployment, and optimization.
BS, MS, or Ph.D. in Computer Science, Statistics, or a related field.
Strong communication, problem-solving, and analytical skills; a collaborative team player.
Deep understanding of ML algorithms, their mathematical foundations, and real-world trade-offs.
Expertise in at least two or more ML domains, including Linear Models, Tree-based Models, Traditional NLP, LLMs, Numerical optimization and Reinforcement Learning.
Hands-on experience with ML frameworks such as Scikit-Learn, TensorFlow, PyTorch, LangChain etc.
Strong programming skills in Python and/or Java, R, Go, Scala.
Experience in SQL, Pandas, and PySpark for efficient data manipulation.
Familiarity with microservice architectures, CI/CD, MLOps best practices.
Nice to Have:
Generative AI: Experience with fine-tuning and optimizing LLMs.
Familiarity with distributed computing frameworks such as Hadoop, Spark, and OpenSearch.
Published research in AI/ML in peer-reviewed journals or top conferences (e.g., NeurIPS, ICML, CVPR).
Prior experience applying AI/ML to cybersecurity use cases.
Basic proficiency in Unix/Linux environments for scripting and automation.
