Data Entry Specialist in United States

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Data Analyst on the Finance team, you’ll play a pivotal role in uncovering the insights that shape company-wide planning, forecasting, and strategic decision-making. This high-impact role blends analytical rigor, technical fluency, and business acumen to steer strategy and identify opportunities for scalable growth. The Finance Data team partners with both Finance and other teams across Vanta. You’ll collaborate closely with stakeholders to build trust and deliver data-driven recommendations; your work will influence everything from operating plans and investment decisions to self-serve reporting and process automation. This is a unique opportunity to deepen your analytics expertise in a dynamic, high-growth environment, with visibility into executive-level priorities and the ability to shape them with data. What you’ll do as a Senior Data Analyst at Vanta: Deliver strategic insights by conducting deep, prioritized analyses that inform high-impact financial decisions. Act as a technical partner to teams across FP&A, Accounting, RevOps, Product, Marketing, and more. Increase team efficiency by automating recurring deliverables and helping scale workflows as the company grows. Empower decision-makers with self-service dashboards and data assets that surface trends and drive informed choices across the business. Advance our analytics infrastructure by partnering with Data Engineering and other analytics teams to democratize access to high quality data and insights. How to be successful in this role: Experience: 4+ years of experience in data analysis or equivalent function. Exposure to FP&A, Accounting, or SaaS

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're hiring a Product Data Scientist to establish how product decisions at Baseten are made with data. You'll work directly with Product and Engineering, alongside GTM to determine measurement, strategy, experimentation and implementation. This is a foundational, hands-on role. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape product strategy. You'll work from clickstream and product events through inference telemetry and observability data, helping Baseten make faster decisions about reliability, performance, adoption and developer experience. RESPONSIBILITIES Partner directly with Product and Engineering: frame the questions that matter, define success criteria, and turn analysis into roadmap, launch, and prioritization decisions. Define how product success is measured: establish metrics across activation, adoption, retention, expansion, reliability and user experience. Support experimentation and launches: design measurement plans, analyze A/B experiments and controlled rollouts, and translate results into product decisions. Diagnose reliability and scaling behavior: join customer signals with request, replica, deployment, and cluster telemetry to find patterns in release bottlenecks, unhealthy replicas, and models without traffic. Define the enterprise customer journey and measure feature adoption

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

Lead Data Scientist Ready to turn bold ideas into real-world impact? At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory , our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI , our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment. Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises. Get to know us at genpact.com and on LinkedIn , YouTube , X , and Facebook . Job Description The Artificial Intelligence Lead Data Scientist is responsible for leading the development and implementation

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.

The Opportunity The world of design is changing rapidly, and the Pro Design team is leading that transformation. We are the Adobe organization behind Illustrator, InDesign, and emerging experiences that connect creativity, collaboration, and AI. Our teams are reimagining what professional design looks like for the next decade - building intelligent, connected tools that empower creators and teams to move faster without sacrificing craft. We are looking for a Senior Business Data Scientist who is creative, analytical, and unafraid to question the status quo and shape the decisions that move key business metrics at scale. Join us and build Adobe’s future products! What you'll Do Map the user funnel and build the metrics, cohorts, and dashboards that Product and Growth rely on to see how users move across free, trial, and paid tiers—and pinpoint where they drop off. Dig into the hard questions (what drives activation, which behaviors predict retention and expansion) and build propensity models for conversion, upgrade, churn, and expansion that feed real-time targeting and in-product nudges. Find and size growth bets and work with Product to ship them. Set north-star, driver, and guardrail metrics with your partners, and stand up multivariate experiments across onboarding, paywalls, in-product prompts, and pricing. What you need to succeed Minimum Requirements: Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar) or equivalent practical experience. 5+ years of experience in data science, product analytics, or a similar quantitative role. Proficiency in SQL and Python (or R) for data manipulation, analysis, and modeling. Hands-on experience designing and analyzing A/B tests and interpre

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each brings together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We are searching for a highly motivated engineer to lead performance benchmarking and optimization efforts for our data center products. You will be instrumental in ensuring our data center solutions deliver industry-leading performance for accelerated computing workloads. What you will be doing: Design and execute comprehensive performance benchmarking strategies for our data center platforms and products Characterize real-world AI training, inference, and HPC workloads at scale Define, track, and report key performance indicators (throughput, latency, efficiency, scaling) Build automation tools and frameworks for performance monitoring and analysis Identify and analyze performance bottlenecks across compute, memory, network and storage subsystems Work closely with architecture, hardware,

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

About Us: Blockworks is an information platform that sits at the center of the crypto industry. We transform raw, complex data and facts into actionable research, trusted alpha-driven insights, and world-class events. The result is transparency and confidence. Blockworks connects investors and businesses in onchain capital markets. We give businesses a platform to earn trust and provide investors with the information they need to underwrite the asset class. Who You Are: Software engineering is your passion, and you have special talents focused on data architecture, design, and API development. You are a player-coach and a natural leader who understands the technical and human elements that go into great software design. You have a results-oriented attitude and a passion for delivering flawless releases and developing digital product pipelines (CI/CD pipelines). You have a proven track record facilitating engineering teams to increase productivity and quality. You're excited at the possibility of helping design and develop our data pipelines as well as leading our data-related projects and strategies for Blockwork's suite of projects. You love moving quickly in a fast-paced start-up, but you also bring intentionality, sustainability and scalability to your approach as an engineer. What You’ll Do: As our Senior Data Engineer , you will be directly responsible for leading the creation and execution of our data models and strategies that feed our products. You'll work collaboratively with other members of the engineering team to design, develop, implement, and evolve our data pipeline and approaches. Every day will look a little different, but in general, you will do things like: Own Data Sourcing Pipelines: You'll be responsible for helping to architect our data warehousing, ingestion and sourcing strategy, working with multiple SDKs to aggregate data from various sources into Blockwork's own data warehouse. Design and Implement ETL Solutions: You'll be responsible for

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is looking for a Senior Data Engineer! This person will be a key member of the growing data team, supporting one of the fastest growing B2B SaaS startups to achieve unicorn status. At Drata, we’re on a mission to help build trust across the internet! Data accuracy is an essential cornerstone of our mission. We are looking for a senior data engineer that can help us strategize

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Our Data and Analytics team is currently looking for a Senior Data Scientist to join us! You’ll be responsible for laying the foundation for a best-in-class business analytics function. You’ll partner closely with our business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. What you’ll do as a Senior Data Scientist at Vanta: Build and maintain trusted product data assets using dbt, Snowflake, and modern analytics infrastructure Leverage AI-powered analytics tools and data agents (e.g., Snowflake Cortex) to accelerate insight generation, automate repeatable analysis, and scale decision-making Define and evolve measurement frameworks for product health, customer lifecycle, and AI-powered product experiences Partner closely with Product, Engineering, Design, and Customer Success to influence product strategy through data Help define Vanta’s analytics strategy and AI measurement practices as our product and data platform evolve Lead executive analytics reviews, translating complex analyses into clear recommendations that drive company decisions How to be successful in this role: 4+ years of experience working with data as a Data Scientist, Product Analyst, or Analytics Engineer in an applied business setting Strong foundation in SQL, Python (or R), statistics, and machine learning Experience designing and evaluating experiments, predictive models, and other statistical analyses to inform product decisions Experience building scalable data assets, metrics, and analytical frameworks on modern cloud data platforms (e.g., Snowflake, dbt) Deep experience with da

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Data Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our engineering team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as a Senior Data Engineer at Vanta: Design and deploy data infrastructure needed to drive data-driven decision-making solutions Design and implement complex data orchestration models, modeling metadata, scaling reporting tools for data science and ML products users Be the company’s expert on data administration, data management and scalable data systems Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses Work with the Product and Enterprise Engineering system teams to structure source systems for reporting consumption across the enterprise Help maintain CDC pipelines to power customer reporting Help develop front end applications to expose analytical data sets enterprise wide How to be successful in this role: Have at least four years of experience working with data and two years of experience in Software Engineering or a related field. Have experience with common analytics tooling (e.g. Stitch/Fivetran, Snowflake/BigQuery/Redshift, dbt, Airflow, Dagster). Have good working knowledge of AWS data infra systems and Terraform. Bring a system-oriented and software engineering mindset to the Data Engineering practice. We’re looking to build frameworks that manage data, and minimize bespoke queries Deep kn

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a Lead Data Scientist on our Analytics and Data Insights team, you'll tackle problems that don't have textbook answers yet; shaping go-to-market strategy for technology that's still being invented, designing the experiments that prove or kill our biggest bets, and helping enterprises understand what foundational AI actually means for their bottom line. You'll own the full analytical lifecycle, from framing the right questions and building the models, to leading a team that delivers answers leadership can act on. As a Lead Data Scientist, you will: Drive the mission forward. Own the science: design and lead experimentation programs including A/B tests, multi-armed bandits, causal inference studies, that directly map to product and go-to-market decisions. Build predictive models that matter: develop and deploy models for forecasting, segmentation, propensity scoring, and opportunity sizing across Cohere's core business lines. Lead and grow a tea

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We're looking for a Staff Data Engineer to own the architecture and technical vision of our data platform. This is a high-leverage, high-autonomy role where you'll set the technical bar for the team, drive cross-functional alignment on data infrastructure strategy, and solve our hardest engineering problems. You'll operate across AWS serverless technologies, Snowflake, dbt, and Terraform, but your impact goes well beyond any single tool: you'll shape how we think about reliability, scalability, cost, and developer experience at the platform level. This role is for someone who doesn't just build great systems, but makes the engineers around them better. The Role: Own the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity. Define and drive the technical roadmap for data infrastructure in partnership with leadership. Design systems at scale : build frameworks, abstractions, and patterns that other engineers use daily. Lead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics. Drive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage. Build and evolve our data pipelines using AWS serverless (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt. Establish and champion engineering standards : observability, testing, CI/CD, code review, and documentation practices. Design and maintain infrastructure for AI/ML workloads , including LLM frameworks, feature pipelines, training

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We’re hiring a highly influential product analytics leader who can turn ambiguous questions into sharp insight, scalable measurement, and recommendations that directly shape what we build. This person will partner closely with Product, Engineering, Design, and Growth to raise the bar on decision quality and establish a more AI-native analytics operating model. Mission Drive the product insight agenda by helping ClickUp make faster, smarter product decisions through rigorous analysis, strong product judgment, and AI-enabled analytics workflows. What You'll Do Own the product analytics agenda across product usage, activation, feature adoption, retention, and expansion, and translate open-ended business questions into structured analyses and clear recommendations Partner with Product, Engineering, and Design to define success metrics early, improve instrumentation quality, and ensure important product surfaces are measurable from launch Build reusable analysis frameworks, semantic layers, metric definitions, and self-serve resources that help product teams answer routine questions faster and more consistently Apply AI-first methods across the analytics workflow, using large language models, coding agents, and automation for tasks like query drafting, QA, validation, documentation, and first-pass synthesis while keeping human judgment at the center of final recommendations Design and interpret experiments, observational analyses, and trend investigations, including situations where data is incomplete or traditional experimentation is not feasible Surface meaningful patterns in behavioral, subscription, and