Roche · 5 hours ago
Data Scientist
Pleasanton, CA
Full-time
Onsite
Mid, Senior Level
$127K/yr - $236K/yrRoche is a global healthcare company dedicated to advancing science and ensuring access to healthcare. They are seeking a Data Scientist with a strong foundation in machine learning, data science, and software engineering to build and deploy ML models and develop AI agents, focusing on unstructured and structured data and workflow automation.
BiotechnologyHealth CareHealth DiagnosticsOncologyPharmaceuticalPrecision Medicine
Responsibilities
Machine Learning and Deep Learning: The candidate must be proficient in a wide range of ML algorithms, from traditional models like linear regression and decision trees to more advanced deep learning architectures such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). They should understand the principles behind model training, validation, and hyperparameter tuning
Natural Language Processing (NLP): For extracting information from unstructured text, strong NLP skills are essential. Look for experience with techniques like tokenization, sentiment analysis, named entity recognition, topic modeling, and using pre-trained language models like BERT, GPT, or others from the Hugging Face ecosystem
Data Handling and Feature Engineering: They should be adept at working with various data formats and have experience in data cleaning, preprocessing, and transforming raw data into useful features for ML models. This includes handling missing values, encoding categorical data, and scaling numerical features
Programming and MLOps: Proficiency in Python is a must, along with a solid understanding of key libraries like Scikit-learn, Pandas, TensorFlow, and PyTorch. Experience with MLOps (Machine Learning Operations) practices, including model versioning, monitoring, and deployment on cloud platforms (AWS, Azure, or GCP), is crucial for building and maintaining robust solutions
AI Agent Architectures: Look for a candidate who understands the components of an AI agent, including a Large Language Model (LLM) as the brain, tools for specific tasks, and a logical structure for decision-making
Workflow Automation: The candidate should have practical experience in designing and implementing automated workflows. This involves integrating AI agents and ML models into existing business processes. They should be able to identify bottlenecks, map out a solution, and build the necessary connectors or APIs to execute tasks automatically
Unstructured Data: The candidate needs to demonstrate expertise in handling various forms of unstructured data, including text, images, and audio. This involves building pipelines to ingest, process, and analyze this data to extract meaningful insights or trigger actions
Qualification
Required
Strong foundation in machine learning (ML), data science, and software engineering
Practical experience in building and deploying ML models and developing AI agents, particularly for tasks involving unstructured/structured data and workflow automation
Proficient in a wide range of ML algorithms, from traditional models like linear regression and decision trees to more advanced deep learning architectures such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
Understanding of the principles behind model training, validation, and hyperparameter tuning
Strong NLP skills for extracting information from unstructured text, including experience with techniques like tokenization, sentiment analysis, named entity recognition, topic modeling, and using pre-trained language models like BERT, GPT, or others from the Hugging Face ecosystem
Adept at working with various data formats and experience in data cleaning, preprocessing, and transforming raw data into useful features for ML models
Experience in handling missing values, encoding categorical data, and scaling numerical features
Proficiency in Python and a solid understanding of key libraries like Scikit-learn, Pandas, TensorFlow, and PyTorch
Experience with MLOps (Machine Learning Operations) practices, including model versioning, monitoring, and deployment on cloud platforms (AWS, Azure, or GCP)
Understanding the components of an AI agent, including a Large Language Model (LLM) as the brain, tools for specific tasks, and a logical structure for decision-making
Practical experience in designing and implementing automated workflows, integrating AI agents and ML models into existing business processes
Expertise in handling various forms of unstructured data, including text, images, and audio
Ability to break down complex business problems into manageable, data-driven solutions
Ability to think critically and creatively to solve real-world challenges
Ability to clearly articulate technical concepts to non-technical stakeholders
Understanding the business context of their work and connecting technical solutions to a positive impact on the company's bottom line or operational efficiency
Benefits
A discretionary annual bonus may be available based on individual and Company performance.
This position also qualifies for the benefits detailed at the link provided below.
Company
Roche
Roche is a pharmaceutical and diagnostics company that offers medicines and diagnostic tests for various medical conditions and diseases.
Founded in 1896
10001+ employees
H1B Sponsorship
Roche has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (12)
2024 (9)
2023 (6)
2022 (2)
2021 (2)
Funding
Current Stage
Public CompanyTotal Funding
$7.79BKey Investors
SoftBankSCALE AINovartis
2021-08-04Post Ipo Equity· $5B
2020-12-07IPO
2020-05-06Post Ipo Equity· $0.5M
Leadership Team
Alan Hippe
Member of the Executive Board - Group CFO
Christine Bakan
Global Head and Group Vice President, Computational Science and Informatics R&D
Recent News
2026-02-05
2026-02-03
Company data provided by crunchbase