Staff Data Scientist, Machine Learning - India

All roles at JumpCloud® are Remote unless otherwise specified in the Job Description. About JumpCloud® JumpCloud® is the AI-powered unified IT management platform designed to secure the modern workforce. By consolidating identity, device, and access management, JumpCloud provides intelligent, secure IT that scales from human users to autonomous AI agents. We help organizations around the globe eliminate complexity and turn AI risk into an optimized advantage, ensuring the right people and agents have secure access to the right resources at all times.   JumpCloud is Intelligent, Secure IT. #LI-PD1 Where you’ll be working/Location: JumpCloud is committed to being Remote First, meaning that you are able to work remotely within the country noted in the Job Description.   This role is remote in the country of India. You must be located in and authorized to work in India to be considered for this role.   Language: JumpCloud® has teams in 15+ countries around the world and conducts our internal business in English. The interview and any additional screening process will take place primarily in English. To be considered for a role at JumpCloud®, you will be required to speak and write in English fluently.  Any additional language requirements will be included in the details of the job description.   Why JumpCloud?   If you thrive working in a fast, SaaS-based environment and you are passionate about solving challenging technical problems, we look forward to hearing from you! JumpCloud® is an incredible place to share and grow your expertise! You’ll work with amazing talent across each department who are passionate about our mission. We’re out of the box thinkers, so your unique ideas and approaches for conceiving a product and/or feature will be welcome. You’ll have a voice in the organization as you work with a seasoned executive team, a supportive board and in a proven market that our customers are excited about.     One of JumpCloud®'s three core values is to “Build Connections.” To us that means creating " human connection with each other regardless of our backgrounds, orientations, geographies, religions, languages, gender, race, etc. We care deeply about the people that we work with and want to see everyone succeed." - Rajat Bhargava, CEO   Please submit your résumé and brief explanation about yourself and why you would be a good fit for JumpCloud®.  Please note JumpCloud® is not accepting third party resumes at this time.      JumpCloud® is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.   Scam Notice: Please be aware that there are individuals and organizations that may attempt to scam job seekers by offering fraudulent employment opportunities in the name of JumpCloud. These scams may involve fake job postings, unsolicited emails, or messages claiming to be from our recruiters or hiring managers. Please note that JumpCloud will never ask for any personal account information, such as credit card details or bank account numbers, during the recruitment process. Additionally, JumpCloud will never send you a check for any equipment prior to employment.   All communication related to interviews and offers from our recruiters and hiring managers will come from official company email addresses (@jumpcloud.com) and will never ask for any payment, fee to be paid or purchases to be made by the job seeker. If you are contacted by anyone claiming to represent JumpCloud and you are unsure of their authenticity, please do not provide any personal/financial information and contact us immediately at recruiting@jumpcloud.com with the subject line "Scam Notice"   #LI-Remote #BI-Remote

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

Understanding of recurring-revenue B2B SaaS business models.

Experience with Data Engineering: Data governance, transformation, and orchestration patterns on modern platforms.