Data Centers And Powered Land Sourcing Lead in United States

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the role We are looking for a Senior Data Engineer to help build and evolve the data platform that powers critical business decisions and customer-facing experiences. You will own significant parts of our data architecture that is main powerhouse of DevRev Computer’s memory for accurate and efficient Answers. As a part of data team, you will design and operate scalable data systems, and work closely with Software Engineering, AI Agent teams, Data Science, and Product teams to turn complex data requirements into reliable, high-quality data products. This role is ideal for an experienced engineer who enjoys solving challenging problems involving large-scale data, distributed systems, database architecture, and performance optimization. You will have significant technical ownership and the opportunity to influence the direction of our agentic data platform while helping raise the engineering bar across the team. Responsibilities Own data architecture for large-scale, high-impact projects, making thoughtful tradeoffs across scalability, reliability, performance, maintainability, and operational cost. Design, build, and operate scalable data pipelines and data systems that reliably ingest, transform, store, and serv

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team The Fraud Partnerships Pod is responsible for overseeing all traditional business development and partnerships for the Anti-Fraud Product Area (PA) at Plaid, focusing primarily on our product partnerships and data acquisition (supply side) efforts. The team supports all products under the Fraud Product Area's purview: IDV, Monitor, Layer, and Protect. About the Role You will have an opportunity to lead the strategy and execution of our supply side and "data in" efforts for our Fraud product area across four products (Plaid IDV, Monitor, Layer, and Protect). You will own all critical data partner relationship management with key stakeholders and be expected to grow them over time. You will be the internal quarterback driving alignment with key major internal stakeholders at Plaid, including Finance, BizOps, Commercial, Legal, and Risk. What You'll Do Spend the majority of your time working hand in hand with product leadership as well as other cross-functional leaders to operationalize our data partners for all fraud products at Plaid. Help our data science and research teams define the source data ecosystem for IDV and Protect according to our 3-year strategy. Help e

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team At Embedded Insights, we find the best machine learning opportunities for external products and internal systems, and collaborate with cross-functional partners to bring them to life. We are a central team of Machine Learning Engineers and Data Scientists. We embed with partner teams to build and apply machine learning models that improve internal decision-making and power the Plaid product suite. About the Role You will be the first Data Scientist on the Embedded Insights team, part of Plaid’s Data organization. You will establish the analytics and metrics backbone for a team supporting a diverse set of internal and external products. You will help drive better decision-making, support machine learning model development, and contribute directly to the health of the Plaid network and the quality of Plaid’s products. Your day-to-day work will include: Analyzing entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks. Creating foundational metrics, dashboards, and monitoring systems that provide a clear view of network health and machine learning model performance. Evaluating the value and performance of machine learni

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to car

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

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

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to carve out the ownershi