Data Scientist

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.