At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description We are seeking a Clinical Data Scientist -RWE Data Analysis Oversight Lead: Inflammation. This position is responsible for the oversight of timeliness and quality of analysis results supporting the CDS-RWE book of work for the Inflammation therapeutic area (TA). This role reports to the CDS-RWE TA Head and supports the scientific leads in implementing strategies to generate analysis results that deliver on portfolio priorities. Serving as the primary point of contact for study and analysis vendors and service vendors, this role is responsible for planning, execution, and quality acceptance of analysis deliverables. The position requires demonstrated experience in managing complex analytical w
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Real people. Real service. At SupplyHouse.com , we value every individual team member and cultivate a community where people come first. Led by our core values of G enerosity, R espect, I nnovation, T eamwork, and GRIT, we’re dedicated to maintaining a supportive work environment that celebrates diversity and empowers everyone to reach their full potential. As an industry-leading e-commerce company specializing in HVAC, plumbing, heating, and electrical supplies since 2004, we strive to foster growth while providing the best possible experience for our customers. We are looking for a Principal Data Architect to join our IT Team. This individual will report into our Vice President of IT, and will be responsible for defining and driving our enterprise data architecture strategy while remaining hands-on in delivering scalable, reliable data products. This role operates at a company-wide scope, shaping long-term data platform direction, governance standards, and scalable architecture patterns that enable analytics, AI/ML, operational systems, and business intelligence. As a strategic individual contributor, the Principal Data Architect will partner with executive leadership, Engineering, Analytics, Security, and Product teams to ensure data is reliable, secure, governed, and positioned as a competitive advantage. This remote position is open to individuals who live in, or are open to relocating to, the following states: Arizona, Delaware, Florida, Georgia, Kentucky, Nevada, New Jersey, New York, North Carolina, Ohio, Rhode Island, South Carolina, Tennessee, Texas, Virginia, and Washington. This position requires travel to our headquarters in Melville, NY 3 times per year for internal meetings and team building activities. Additional travel may be required based on department and company needs. We reimburse reasonable and necessary travel expenses, and you’re also welcome to work on-site anytime beyond these visits – our doors are always open. Role Type: Full-Time, Exemp
Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. Role Summary: We are looking for a talented and detail-oriented Sr Data Engineer to tackle data challenges. You will design, build, and maintain critical data pipelines and datasets, supporting areas like recruiting, compensation, talent management, and learning and development. Your work will enhance data accessibility and empower the People Team and business leaders to make informed decisions with high-quality, reliable data. Key Responsibilities: Develop and maintain robust data pipelines and datasets. Build foundational data products for key business areas. Enhance self-service data capabilities for the People Team. Ensure high standards in ETL/ELT operations, data quality, and pipeline reliability. Join us to drive impactful change and support SoFi's mission of fostering a thriving workplace through data excellence. What you’ll do: Design and build production dbt models in Snowflake that integrate Workday and other People systems into well-modeled, documented datasets, including slowly changing dimensions for People history. Build and operate Airflow DAGs that ingest People systems data and orchestrate dbt runs, keeping loads reliable and re-runnable. Own data quality and observability: dbt tests, freshness checks, row-count validation, and monitoring so issues are caught before stakeholders see them.
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf
AVP - Data Governance Foundation Sr Analyst — SHIVAJI GARDENS, MOONLI. Apply via Workday.
The Ontology Engineer is a foundational technical hire on the AI, ML and Data Science team specializing in Knowledge Representation. This role is responsible for designing and maintaining the formal ontological architecture that makes cross-organizational data alignment. This is not a taxonomy or metadata management role. It requires genuine formal depth in description logics, upper ontology theory, and the ability to reason about what an ontology commits to and what it leaves open. Our platform sits between hospitals, distributors, GPOs, manufacturers, and regulators, enabling transactional execution, clinical data alignment, and analytics optimization across organizational boundaries. Each party maintains its own implicit ontology encoded in its schemas, workflows, and data. The Ontology Engineer will define the formal structures and processes that make alignment across them possible. These structures should be auditable, compositionally sound, and maintainable over a multi-year lifecycle as all parties' systems evolve. This Engineer will work directly with teammates that are familiar with ontology formalisms and with domain experts who understand the operational realities of HCSC data. They will be expected to make and defend design decisions at the level of formal correctness, not just practical convenience, and to direct and evaluate LLM-assisted ontology discovery and enrichment pipelines with the rigor that formal alignment demands. Essential Duties: Design and maintain the ontology, covering the canonical structural layer (organizations, items, contracts, transaction), source data ontologies (supporting the canonical) and the process layer (data curation, ontology matching, workflows). Establish the rules for when two records from different systems refer to the same thing, and when they don't — recognizing the answer can differ by use case. Establish mappings from trading partner source data to the canonical ontology, with documented proven
As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improveme
Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Coinbase is building the future of institutional trading as part of the Everything Exchange, powering the systems that let the world's largest financial institutions trade across markets with speed, depth, and trust. As a Staff Data Engineer, Market Data on the Institutional Markets team, you'll architect, build, and own the systems that generate, capture, normalize, and distribute real-time market data across Coinbase at low latency - the ticker plant and distribution backbone of a unified trading platform - while leading a lean, high-impact team. It's a rare chance to architect market data infrastructure from the ground up, with the ownership of a startup and the reach of Coinbase. What you'll do: Build and operate market data components: feed handlers, normalization, distribution, and venue connectivity. Design low-latency, high-throughput systems for real-time market data used by trading systems. Strengthen reliability and performance by contributing to observability, on-call, and incident response. Write high-quality, well-tested code and raise the quality bar on a lean team. Partner with engineers, product, and cross-functional stakeholders to deliver market data capabilities. Required Skills and Experience: 5+ years of backend engineering, with experience building and maintaining production low-latency systems. Hands-on experience with market data systems (fee
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team When a Fortune 500 hands its customer experience to an AI agent, it is one of the largest bets the business will make that year — and enterprises of that size do not make it on a demo. Each customer has their own requirements for how an AI agent should be evaluated, and the narratives we build have to start there and hold up long after the decision is made. Data plays a central role in almost every one of those narratives, which is why Agent Data Science exists. A deployment is evaluated by many stakeholders inside the customer's organization, including senior leaders, customer experience teams, and technical functions, each with their own criteria for success. You own how performance is defined, measured, and demonstrated against these criteria, from translating them into metrics we operationalize and deliver, to improving the ones that are key to each evaluation. You hold that from the first pre-sales evaluation through the life of the account. Our team sits within Agent Product Ma
About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow
Associate Data Manager, Clinical Data Sciences — India - Chennai. Apply via Workday.
Clinical Data Management Manager — United States - California - Foster City. Apply via Workday.
Manager – Data Platform — Hyderabad, Telangana, India. Apply via Workday.
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: Human Data powers model training and evaluation by producing high-quality human-generated data at scale. This role focuses on the metrics, systems, and operating insights that help Human Data run efficiently—spanning workforce performance, capacity and allocation, operational process health, and decision-making support for cross-functional partners. Our ideal candidate is a proactive analyst with strong quantitative skills and operational judgment, able to turn incomplete data into clear recommendations that improve throughput, quality, cost, and reliability. You will partner with operations leaders, engineering stakeholders, and enabling teams to identify problems, build operating systems, and drive improved planning decisions. RESPONSIBILITIES: Perform analyses of Human Data operational metrics—such as capacity, utilization, quality, throughput, cycle time, cost efficiency, and workforce health—to uncover trends, risks, and opportunities. Build and maintain reporting, trackers, and dashboards that make core operating KPIs visible and actionable for managers and cross-functional partners. Develop and improve planning and forecasting views (e.g., demand signals,
SMAI Data Scientist — Fab 10A, Singapore. Apply via Workday.
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