Staff Data Scientist, Machine Learning - India at JumpCloud
JumpCloud is hiring a Staff Data Scientist, Machine Learning - India in Bengaluru, India. Remote.
About JumpCloud
JumpCloud is a unified IT management platform for identity, access, and device management. It enables organizations to manage Windows, Apple, Linux, and Android devices and provides secure access features such as single sign-on (SSO), multi-factor authentication (MFA), Zero Trust, and RADIUS. The platform also supports agentic IAM, allowing organizations to govern and connect AI agents to infrastructure, applications, and enterprise data. It is designed to manage both human users and autonomous AI agents from a single platform.
Staff Data Scientist, Machine Learning - India job description
About JumpCloud®
JumpCloud is Intelligent, Secure IT.
About the Role
We are seeking a hands-on Staff Data Scientist to architect and execute Machine Learning solutions, develop Large Language Models (LLMs), and build the AI stack to automate complex Data Analytics workflows. This role is at the heart of JumpCloud's applied-AI journey, combining deep foundations in classical machine learning with practical experience in building AI agents and systems that transform business decision-making and analytics delivery.
What We Are Looking For:
Professional Experience: 8+ years across analytics, LLMs, data science, and applied machine learning, with a proven track record of owning business-facing solutions.
Product-Focused ML: Experience developing real-time anomaly detection models and large-scale data processing systems to identify product usage signals and adoption patterns.
Business ML Applications: Ability to solve business problems using predictive and prescriptive modeling, including price sensitivity, churn, revenue forecasting, and marketing mix optimization.
Domain Expertise: Knowledge of identity threat signals (e.g., unusual logins, MFA behavior, authentication velocity) and analyzing deviations from historical user behavior.
AI Execution & Advisory: Expertise in managing AI service costs and relevance, building AI agents for automated analysis, and generating explainable insights within business workflows.
Analytics Foundations: Strong background in segmentation, root cause analysis, funnel optimization, and acquisition quality scoring to drive growth and efficiency.
Thought Leadership: Capability to reason through unfamiliar domains to identify potential signals, features, and modeling approaches independently.
Ecosystem Background: Experience in fast-paced, data-first environments or startups where ML is a core driver of business outcomes.
What You Will Own:
AI Stack Roadmap: Leading the path from opportunity sizing and prototyping through to evaluation, deployment, and impact measurement.
Technical Execution: Ensuring robust performance, validation, and inference of real-time models using the latest industry improvements.
Standards & Governance: Establishing pragmatic standards for model development, LLM evaluation, observability, security, and cost management.
Capability Mentorship: Coaching analysts and creating reusable tools to raise the collective quality of predictive problem-solving.
Strategic Communication: Translating complex technical work into clear recommendations and trade-offs for senior stakeholders.
Cross-Functional Leadership: Aligning stakeholders with competing priorities and creating clarity in ambiguous settings to influence outcomes.
Technical Breadth:
Expertise in Python, SQL, statistical analysis, and common ML frameworks.
Deep knowledge of MLOps, including feature engineering, deployment, inference, and monitoring.
Proficiency with LLM APIs, RAG, Semantic Layers, Embeddings, and agent orchestration frameworks.
Experience building robust ML pipelines for both real-time and asynchronous predictions.
Behavioral Strengths
Preferred Qualifications
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