Senior Data Scientist

Omnissa•Mountain View, CA

9d•$146,287 - $304,750•Hybrid

About The Position

We are Omnissa. Omnissa is the first AI-driven digital work platform, built to support flexible, secure, work-from anywhere experiences. We integrate industry-leading solutions—including Unified Endpoint Management, Virtual Apps and Desktops, Digital Employee Experience, and Security & Compliance—into a seamless, autonomous workspace that adapts to how people work. Our platform boosts employee engagement while optimizing IT operations, security, and cost. Guided by our Core Values— Act in Alignment, Build Trust, Foster Inclusiveness, Drive Efficiency, and Maximize Customer Value — we’re growing rapidly and committed to delivering meaningful impact. If you're passionate about shaping the future of work, we’d love to hear from you. Our platform manages millions of devices across multiple operating systems, requiring exceptional performance, scalability, availability, and resilience. You will join the AI Platform Team, the group responsible for building foundational AI capabilities across the Omnissa product ecosystem. As a Senior Data Scientist, you will lead and innovate within the data science team to drive significant advancements in our AI/ML and data analytics capabilities. This is a hands-on role, and you will be expected to develop AI/ML based solutions, work closely with cross-functional teams to solve complex business problems, and contribute to the company’s vision through advanced analytics, machine learning, and artificial intelligence. You’ll work closely with engineering and product teams to operationalize models across our cloud scale environment while driving best in class ML engineering practices.

Requirements

5+ years of experience in data science or machine learning engineering roles.
Hands-on experience with one or more of the following areas is required; experience across multiple areas is strongly preferred: supervised and unsupervised learning, classification and regression, clustering, time-series analysis, anomaly detection, recommendation systems, reinforcement learning, information retrieval, and natural language processing (NLP).
Highly proficient in Python and working knowledge of at least one other programming language such as Java, C++.
Extensive experience with AI/ML frameworks and libraries such as Scikit-Learn, Numpy, Pandas, SciPy, Hugging Face Transformers.
Hands-on experience with Large Language Models (LLMs), including finetuning, prompt engineering, and deployment.
Knowledge of text embedding models and vector databases for Retrieval Augmented Generation (RAG) systems.
Experience with orchestration frameworks (e.g., LangChain/LangGraph) to build AI agents and multi-agent systems.
Familiarity with cloud platforms and tools such as AWS, Azure, of Google Cloud for development and deployment of scalable AI/ML models.
Experience with distributed computing frameworks (e.g., Spark, Ray).

Nice To Haves

experience across multiple areas is strongly preferred

Responsibilities

Lead the design and development of advanced data science and machine learning analytics models using structured, unstructured and semi-structured data.
Work with engineers to design and implement scalable machine learning pipelines, covering all stages from data ingestion and feature extraction to training, testing, validation, inference, and continuous learning in production systems.
Leverage key technologies and state-of-the-art tools necessary for exploring/querying data, visualization, and advanced analytics - distribution of key attributes, relationships between attributes, feature engineering, and statistical analyses.
Be an expert in and lead the development of AI/ML solutions based on Large Language Models (LLMs), Retreival Augmented Generation (RAG), and AI Agents.
Optimize ML models and pipelines for performance, scalability, reliability, and cost efficiency.
Design and implement prompt engineering strategies to optimize the performance of LLM based applications.
Collaborate with cross functional teams to integrate ML solutions into core platform features and services.