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10 results for Data Scientist in Oakland, CA

Data Engineer

San Francisco, CA
remote
Temporary / Contract
65 - 70 USD / Hourly
We are looking for a Contract Data Engineer to support financial systems and data operations in San Francisco, California. This is a remote on-going contract. This role will work across Finance, Systems, and Engineering to improve data reliability, strengthen integrations, and enhance platforms that support billing, accounts payable, and quote-to-cash workflows. The ideal candidate brings deep technical expertise with NetSuite and Snowflake, along with strong coding skills to diagnose issues, streamline processes, and build scalable solutions in a complex systems environment. Responsibilities:• Build, monitor, and refine data pipelines that move financial and transactional information across internal platforms and enterprise systems.• Investigate data issues, resolve integration failures, and improve the overall accuracy and consistency of business-critical datasets.• Develop and maintain middleware solutions that connect NetSuite, Salesforce, Snowflake, and custom applications.• Partner with Finance, Systems, and Engineering stakeholders to deliver technical enhancements that support accounting operations and downstream reporting.• Implement improvements within NetSuite and related financial systems to better support billing, accounts payable, and quote-to-cash processes.• Troubleshoot code and system behaviors using SQL, Python, and related tools to identify root causes and restore reliable performance.• Support integration workflows between Salesforce and NetSuite, ensuring stable data exchange and operational continuity.• Evaluate and contribute to automation initiatives, including AI-enabled workflow opportunities that can reduce manual effort and improve efficiency.
2026-08-19T00:00:00Z

Data Analyst

San Francisco, CA
remote
Temporary / Contract
35 - 40 USD / Hourly
We are looking for a Data Analyst to support reporting, dashboard development, and business-focused data investigations for a financial services team. This long-term, remote contract position is based in San Francisco, California, and offers the opportunity to work remotely while partnering closely with stakeholders to deliver clear, timely insights. The ideal candidate brings strong analytical expertise, hands-on experience with modern BI tools, and the ability to manage priorities effectively in a fast-paced, sprint-driven environment. Responsibilities:• Create and refine recurring reports and analytical outputs that help business partners make informed decisions.• Develop, update, and enhance dashboard solutions in Looker to meet evolving stakeholder needs.• Investigate data questions and resolve reporting issues related to business operations and client-focused requests.• Manage assigned work within a sprint-based workflow, handling incoming tickets and adjusting priorities as needed.• Collaborate with cross-functional stakeholders to gather requirements, confirm scope, and communicate delivery timelines.• Provide ongoing analytics support through BI and reporting platforms, translating data into actionable insights.• Maintain a balanced workload between stakeholder coordination and hands-on analysis, ensuring both communication and execution remain strong.
2026-08-18T00:00:00Z

Data Scientist II

San Ramon, CA
remote
Permanent / Full Time
119000 - 180000 USD / Yearly
Our client is seeking a Data Scientist II – Generative AI to join a cutting-edge team focused on building scalable, production-ready AI solutions that transform business workflows and deliver measurable impact across global operations. This role is ideal for professionals passionate about leveraging Generative AI technologies, creating intelligent agents, and driving innovation at scale. You will design and implement GenAI-powered agents that streamline internal processes, enhance productivity, and support business development initiatives. Responsibilities include developing robust prompt engineering frameworks, building RAG pipelines, and converting prototypes into production-ready solutions. You’ll collaborate closely with engineering and business teams to ensure solutions meet diverse client needs and are optimized for global deployment. Key projects include extending the company’s GPT platform, creating AI agents that improve efficiencies for RFP development, onboarding materials, and SOW requirements. Success in this role means quickly ramping up on backlog projects, delivering high-priority initiatives, and staying ahead of emerging GenAI frameworks to continuously advance internal AI capabilities.
2026-08-18T00:00:00Z

Data and Knowledge Engineer

Menlo Park, CA
onsite
Permanent / Full Time
200000 - 300000 USD / Yearly
Data & Knowledge Engineer Company OverviewA leading artificial intelligence and advanced analytics organization is seeking a Data & Knowledge Engineer to help power next-generation AI and decision-support platforms. Based in Los Angeles, California, the company specializes in integrating complex data from disparate sources into unified intelligence systems that support advanced analytics, automation, and operational decision-making. This is an opportunity to work on mission-critical initiatives involving large-scale data, knowledge graphs, and AI-driven applications. Role SummaryThe Data & Knowledge Engineer will lead the onboarding, transformation, and governance of complex multimodal data into scalable data and knowledge platforms. This role focuses on integrating structured and unstructured data sources, designing reusable data pipelines, developing entity resolution frameworks, and enabling high-quality data for analytics, retrieval, AI workflows, and geospatial applications. The ideal candidate combines strong data engineering expertise with experience in knowledge graphs, data quality, and large-scale information management. Key Responsibilities<ul><li>Design and develop scalable data ingestion pipelines for structured, unstructured, geospatial, and sensor-based data sources.</li><li>Build and maintain batch and streaming data processing systems across cloud, on-premises, and disconnected environments.</li><li>Develop integrations with APIs, databases, file systems, enterprise applications, and external data sources.</li><li>Design schema mapping, normalization, and transformation processes that support diverse customer data models.</li><li>Implement entity resolution, record linkage, deduplication, and data matching capabilities across multiple sources.</li><li>Preserve data lineage, provenance, auditing, and traceability throughout the data lifecycle.</li><li>Create data validation, monitoring, replay, and exception-handling processes for complex data environments.</li><li>Develop workflows for managing ambiguous records, conflicting information, and data quality issues.</li><li>Define and measure data quality metrics, onboarding effectiveness, and operational performance indicators.</li><li>Support knowledge graph, retrieval, AI, and analytics capabilities through high-quality governed datasets.</li><li>Partner with engineering and stakeholder teams to transform recurring onboarding requirements into reusable platform capabilities.</li><li>Contribute to platform architecture, engineering standards, and long-term data strategy initiatives.</li></ul>Additional Details<ul><li>Fully onsite 5 days a week</li><li>Full-time exempt position</li><li>Hands-on engineering role with substantial ownership and technical influence</li><li>Opportunity to work on large-scale data, knowledge graph, and AI-driven initiatives</li><li>Staff-level candidates may provide architectural leadership, mentorship, and engineering guidance</li><li>Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements</li></ul>
2026-08-19T00:00:00Z

Business Analytics/Data Analyst

San Ramon, CA
remote
Temporary / Contract
75 - 90 USD / Hourly
Robert Half Management Resources is looking for a Business Analytics/Data Analyst to support one of our clients on an interim basis. This role will contribute to Workday supply chain and procurement efforts by improving data quality, validating converted records, and resolving issues that affect system readiness. The position works closely with project stakeholders to ensure legacy information is accurately prepared, tested, and aligned with business rules in the target environment. Responsibilities:• Prepare, map, and transform legacy supply chain and procurement data for upload into Workday using approved conversion tools and templates.• Perform detailed comparisons between source records and Workday data to confirm completeness, accuracy, and adherence to defined business rules.• Investigate conversion failures and data-related defects, identify root causes, and coordinate fixes for issues affecting inventory, suppliers, requisitions, and purchasing records.• Partner with functional leads, analysts, and implementation team members to address data discrepancies and keep conversion activities moving on schedule.• Support unit, integration, and broader testing cycles by building reliable data sets and confirming converted information performs correctly in test environments.• Use Excel, SQL, and related analysis tools to cleanse, reconcile, and organize large datasets for migration and validation activities.• Track issues in project management or defect logging tools and provide clear updates on status, findings, and resolution progress.
2026-08-17T00:00:00Z

Data Engineer III

San Ramon, CA
remote
Permanent / Full Time
104000 - 153000 USD / Yearly
Robert Half, one of FORTUNE’s World’s Most Admired Companies and a Fortune 100 Best Companies to Work For is hiring for a Data Engineer III to join the ATI Data Science Innovation department. Solution Design & Technical Leadership<ul><li>Lead architecture and design of complex data pipelines on Databricks lakehouse architecture (Unity Catalog, Delta Lake, Structured Streaming)</li><li>Define technical approach for data engineering initiatives, mentor less-senior engineers, and set standards for code quality through leadership and code reviews</li><li>Design and build data foundations that enable AI/ML capabilities — feature stores, embedding pipelines, vector search indexes, and model training datasets</li><li>Align data engineering solutions with business strategy, including support for Agentic AI workloads</li></ul>Data Infrastructure & Platform<ul><li>Own health, scalability, and modernization of data infrastructure with Databricks as the strategic platform — including workload migration, compute optimization, and Unity Catalog adoption</li><li>Optimize pipeline performance (Delta Lake table layouts, clustering, Z-ordering) and establish monitoring/alerting best practices with clear SLAs</li><li>Build data infrastructure supporting Agentic AI systems — real-time data access layers, context retrieval pipelines, and agent-accessible data services</li><li>Collaborate cross-functionally with DevOps, Platform Engineering, and MLOps roles to integrate data solutions into the broader technology environment and shared AI infratstructure – Mlflow registries, feature stores, and agent orchestration layers</li><li>Provide consultation to Senior Leadership on complex projects and drive continuous improvement initiatives</li></ul>Data Quality, Governance & Collaboration<ul><li>Champion data governance at all layers for data, models, and AI assets</li><li>Implement data quality strategies (master data management, validation rules, Delta Live Tables expectations) to ensure trust in enterprise data</li><li>Serve as liaison across data engineering, AI engineering, and business teams; promote data literacy and stewardship</li></ul>
2026-07-30T00:00:00Z

Machine Learning Engineer

Menlo Park, CA
onsite
Permanent / Full Time
200000 - 300000 USD / Yearly
Machine Learning Engineer Company OverviewBased in Los Angeles, California, the company specializes in transforming complex, multi-source data into actionable insights through machine learning, knowledge graph technologies, and advanced analytics. This is an opportunity to work on mission-critical applications in a highly collaborative environment focused on innovation, scalability, and operational excellence. Role SummaryThe Machine Learning Engineer will play a critical role in designing, training, deploying, and optimizing machine learning models that operate on large-scale temporal, geospatial, relational, and unstructured datasets. This position requires an experienced engineer who can independently own the full machine learning lifecycle, from dataset development and model architecture selection to deployment, monitoring, and continuous improvement. The ideal candidate brings broad expertise across computer vision, natural language processing (NLP), geospatial analytics, MLOps, and large-scale production machine learning environments. Key Responsibilities<ul><li>Design, train, evaluate, deploy, and optimize machine learning models across multiple production use cases.</li><li>Build predictive solutions for anomaly detection, forecasting, entity resolution, relationship prediction, risk assessment, and operational decision support.</li><li>Partner with data engineering teams to develop high-quality training datasets from structured, unstructured, temporal, relational, and geospatial data sources.</li><li>Design model architectures and select appropriate algorithms based on business objectives, data characteristics, and operational requirements.</li><li>Develop and maintain machine learning pipelines spanning data preparation, feature engineering, training, evaluation, deployment, and monitoring.</li><li>Build scalable solutions that leverage graph-based and knowledge graph-driven data architectures.</li><li>Develop models utilizing computer vision, NLP, geospatial analytics, and predictive modeling techniques.</li><li>Establish rigorous evaluation frameworks, baselines, performance metrics, and validation methodologies.</li><li>Design experiments that mitigate data leakage, model drift, bias, and changing data distributions.</li><li>Implement monitoring, observability, alerting, retraining, rollback, and model governance processes.</li><li>Maintain reproducible datasets, model artifacts, evaluation results, and deployment workflows.</li><li>Collaborate with distributed engineering teams to deliver reliable and scalable machine learning capabilities.</li><li>Improve model calibration, confidence scoring, uncertainty estimation, and explainability.</li><li>Contribute to technical architecture, machine learning standards, and long-term platform strategy.</li></ul>Additional Details<ul><li>Fully onsite 5 days a week</li><li>Highly collaborative environment with strong emphasis on machine learning, knowledge graphs, and data-driven decision support</li><li>Opportunity to influence technical direction, machine learning standards, and model lifecycle practices across multiple initiatives</li><li>Candidates must be authorized to work in the United States and satisfy applicable regulatory employment requirements</li></ul>
2026-08-19T00:00:00Z

Staff Data Platform Engineer

San Francisco, CA
remote
Permanent / Full Time
200000 - 250000 USD / Yearly
100% Remote!! We are looking for an experienced Staff Data Platform Engineer to lead the design and long-term direction of a foundational data platform in San Francisco, California. In this role, you will shape how critical operational data is modeled, governed, and accessed to support automation in a highly regulated healthcare environment. You will combine architectural leadership with hands-on engineering to build reliable, scalable systems that enable product teams to move quickly while maintaining accuracy, performance, and audit readiness. Responsibilities:• Lead the architecture and ongoing refinement of core data structures, including business entities, system events, and traceable records for automated outcomes.• Develop and maintain the platform services and storage layers that support AI-enabled workflows, ensuring data is both usable for decision-making and controlled for compliance needs.• Create approaches for organizing, versioning, and retrieving domain knowledge so the platform can expand in capability as product needs evolve.• Define stable data interfaces and platform APIs that allow engineering teams to build new functionality against dependable contracts.• Improve scalability and system resilience to support rapid growth in users, workload volume, and transaction complexity.• Partner with product and engineering leaders to set technical priorities, evaluate tradeoffs, and guide platform strategy.• Write production-quality backend code and contribute directly to implementation across the data platform stack.• Strengthen observability, testing, and data quality practices to protect integrity and support effective incident response.
2026-07-31T00:00:00Z

DevOps Engineer

San Francisco, CA
onsite
Permanent / Full Time
180000 - 215000 USD / Yearly
We are looking for a Senior or Staff DevOps Engineer to strengthen our engineering organization in San Francisco, California. In this role, you will improve the foundation that supports application delivery, platform reliability, and developer productivity across cloud-based systems. You will work closely with engineering partners to create scalable infrastructure, streamline release processes, and build dependable operational practices that support continued growth. Responsibilities:• Architect and maintain cloud infrastructure using infrastructure-as-code practices that promote consistency, scalability, and operational simplicity.• Create and refine automated delivery pipelines to support dependable, efficient releases across multiple services and environments.• Establish repeatable deployment approaches for serverless applications, container-based platforms, and orchestrated workflows.• Build internal automation and developer tools that reduce manual effort and help backend and machine learning teams work more efficiently.• Enhance development, testing, and staging environments to improve workflow speed and reduce friction during software delivery.• Define strong monitoring and observability practices across logs, metrics, and tracing to improve system visibility and troubleshooting.• Investigate reliability, latency, and performance issues in distributed environments and partner with engineers to implement lasting improvements.• Strengthen operational readiness by supporting incident response, contributing to post-incident reviews, and turning findings into better tooling and processes.• Integrate security and compliance controls into infrastructure and deployment workflows, including access management, patching, and vulnerability remediation.
2026-08-11T00:00:00Z

AI Engineer (AI Data Privacy, Security & Governance)

San Ramon, CA
remote
Permanent / Full Time
85000 - 124000 USD / Yearly
obert Half is seeking a Software Engineer II – AI Engineer to analyze, design, program, debug, test, implement, and support the privacy, security, and governance controls that protect generative AI technologies. This role safeguards GenAI-enabled applications, including LLM-powered workflows, RAG pipelines, plugins, skills, and autonomous agents, by embedding data protection, security guardrails, and responsible AI governance across the development lifecycle. This role supports SDLC documentation across all phases, with a focus on data privacy, security guardrails, governance, compliance, and risk management. It also works with users to define requirements and support applications in production. What You’ll Do <ul><li>Design and implement data privacy controls, including PII/PHI detection, redaction, and data minimization. </li><li>Build security guardrails, including prompt-injection defense, jailbreak prevention, and output filtering. </li><li>Establish governance for plugins, skills, and agents, including registration, approval, and lifecycle management. </li><li>Review and vet third-party plugins, skills, and agent tools for security, privacy, and compliance risks. </li><li>Define and enforce access controls, authentication, and least-privilege permissions for AI components. </li><li>Implement guardrails for autonomous agents, including action scoping, tool-use restrictions, and human-in-the-loop approval. </li><li>Apply data classification, retention, and residency policies across GenAI data flows. </li><li>Monitor AI systems for policy violations, data leakage, and anomalous plugin, skill, or agent behavior. </li><li>Maintain audit trails and logging for plugin, skill, and agent activity. </li><li>Support compliance with regulations and frameworks, including GDPR, CCPA, and the EU AI Act. </li><li>Provide Level II production support for security, privacy, and governance incidents. </li><li>Support incident response, including containment, escalation, and remediation. </li></ul>
2026-08-18T00:00:00Z