Senior Data Scientist

Job summary: As a Senior Data Scientist for Messaging App, you will play a critical role in developing and deploying machine learning models to enhance the security, productivity, and intelligence of our messaging platform. You will work on a variety of challenging problems, from detecting and preventing fraud and abuse to building intelligent agent solutions that assist users within the chat environment. You will have a strong background in classical machine learning techniques, natural language processing (NLP), and experience with both large language models (LLMs) and small language models (SLMs). You will work closely with product managers, engineers, and other data scientists to deliver impactful data-driven solutions. Key Responsibilities:Model Development & Deployment: Design, develop, train, evaluate, and deploy machine learning models for a variety of applications within KChat, including:   ■ Security:          ● Fraud detection and prevention (e.g., identifying phishing scams, spam,                      malicious links).          ● Abuse detection (e.g., identifying hate speech, harassment, and other policy              violations).          ● Account takeover detection.          ● Anomaly detection.  ■ Productivity:          ● Smart reply suggestions.          ● Message summarization.          ● Task automation (e.g., scheduling meetings, setting reminders).          ● Content recommendations.          ● Translation.        ■ Agent AI:              ● Building and integrating intelligent agent solutions (chatbots) within KChat                    to assist users with various tasks.              ● Developing natural language understanding (NLU) and dialogue     management capabilities for agents.             ● Fine-tuning and customizing LLMs and SLMs for specific tasks and domains. Work with large datasets of text, user activity, and other relevant data. Implement data preprocessing, feature engineering, and model selection techniques. Use a variety of machine learning algorithms, including classical ML models (e.g., logistic regression, SVM, random forests), deep learning models (e.g., transformers, LSTMs), and language models (LLMs and SLMs). Deploy models to production and monitor their performance. Data Analysis & Insights: Analyze user behavior and messaging data to identify opportunities for improvement. Communicate findings and recommendations to product and engineering teams. Collaboration: Work closely with product managers to define product requirements and translate them into data science solutions. Collaborate with engineers to integrate models into the KChat platform. Work with other data scientists to share knowledge and best practices. Research & Innovation: Stay up-to-date on the latest data science and machine learning research. Explore and evaluate new techniques and technologies.