Data Steward Jobs

Data Analyst V itD is seeking a Data Analyst V to analyze customer experience and customer support data for Reality Labs, uncover actionable insights, and improve customer satisfaction across the end-to-end customer journey. The ideal candidate will bring 8+ years of experience in data analytics or data science, strong SQL and Python or R programming skills, and expertise in statistical modeling, predictive analytics, and Generative AI to translate complex customer data into insights that drive business improvements and customer-centric decisions. Location : Remote – US (Candidates must be able to work Central or Pacific Time hours) Duration : 12 months, with potential for extension or conversion Schedule : 40 hours per week, Monday–Friday; no overtime. We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities Analyze large, complex datasets using SQL, Python or R, and statistical techniques to identify customer experience trends, pain points, and opportunities for improvement. Synthesize customer signals from surveys, digital analytics, behavioral data, operational metrics, and customer support interactions across the end-to-end customer journey. Apply statistical modeling, predictive analytics, machine learning, and natural language processing (NLP) to analyze customer support conversations, transcripts, and tickets to generate actionable insights. Develop customer segmentation and clustering models to identify common customer issues and recommend targeted solutions, including self-service resources. Integrate customer feedback with transactional, operational, and behavioral data to identify key drivers of customer satisfaction and business outcomes. Design, test, and launch customer experience and support metric scorecards to track KPIs and evaluate performance across digital, AI-powered, and human-assisted sup

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. Algorithms Engineer | PhD Holder Only 5 Work Days Per Week Office Near Tai Seng MRT , Singapore Medical Benefits Provided Entitled to Yearly Bonus & Performance Bonus Job Requirements: PhD Holder in Computer Science, Applied Mathematics, Electrical Engineering, Pattern Recognition, Artificial Intelligence, Automatic Control, Operations Research, Biology, Physics / Quantum Computing, Neuroscience, Statistics or a related field. Familiar with common machine learning and deep learning algorithms and keeping track with the latest SOTA implementations . Strong programming skill in Python, C / C++ , proficient in mathematical / statistical concepts and exceptional coding skills Hands-on experience with AI / ML frameworks be familiar such as Caffe, PyTorch, TensorFlow, MxNet etc. Have rich project experience in machine learning and deep learning , be familiar with common algorithm models, such as CNN, RNN, LSTM, Transformer, ViT, etc., and be able to improve and innovate models according to actual problems. Experience in familiar the design, parameter tuning and optimization methods of neural network models is a plus Experience in model compression and in the transplantation and optimization of deep learning forward inference on various platforms, including NPU / G

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The opportunity: Flexport is looking for a creative, technically-minded Senior Data Scientist who is excited about solving challenging problems in fulfillment and logistics. We provide ecommerce merchants a full range of "factory to door" logistics solutions. This role focuses on building automated decision-making processes that ensure that we meet or exceed the expectations of our merchants for fulfillment speed and reliability, while growing the network in a cost-efficient way. Data is at the heart of our business, and as a Data Scientist, you will develop first-in-class science products to make fulfillment easy and efficient for our merchants. In collaboration with multidisciplinary product, engineering, and business/operations teams, you will apply advanced Operations Research (OR) and Machine Learning (ML) methods to deliver data-driven insights and automated decision-making solutions in Flexport’s fulfillment products. Our business, product, and engineering teams collaborate closely with our Data Scientists to share domain knowledge, test hypotheses at scale, and develop promising solutions that can be quickly and widely deployed. We are passionate about prov

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: This Data Visualization Engineer is a versatile, hands-on builder who owns how 𝕏 turns data into decisions. They will administer our current BI platform, build dashboards quickly, and partner with the business to shape a modern, unified reporting and analytics solution. RESPONSIBILITIES: Business-critical responsibilities include, but are not limited to: Administering our BI platform (currently Tableau Server) as its sole administrator: upgrades, patches, maintenance, license management, SSO, and data drivers Supporting 12 department sites and their Site Admins, plus about 700 users, including owning the tbl-site-admins and tableau Slack channels Handling all BI requests through Slack and Jira (about 12 a week): access, ownership changes, data source issues, troubleshooting, and fixing bugs Communicating proactively with Site Admins, users, and developers about downtime, upgrades, and widespread issues Quickly designing and building dashboards and data products that turn complex data into clear, decision-ready insight Maintaining an inventory of existing reports and dashboards and working with business owners to decide what to migrate, rebuild, or retire Helping

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Software Engineer, Data to be a technical powerhouse to help us scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will… Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because… 3+ years of professional experience 3+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Proficiency in programming languages such as Python/Kotlin/Scala 3+ years of experience in ETL orchestration and workflow management tools like Airflow Expert in database fundamentals, SQL, data reliability practices and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kafka/Flink/Spark Streaming Excellent communication skills and experience working with technical and non-technical teams and knowledge of reporting tools Comfortable working in

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role You'll be one of the founding data scientist on Replit's Growth team, working with Product and Engineering leadership across acquisition, activation and recommender systems, and helping shape how Replit experiments. This role is for someone who doesn't wait to be asked. You spot problems and opportunities before anyone else does, bring a strong point of view, and push it until it changes what we build. You will: Own data science for major growth areas, partnering with PMs and engineers from problem framing and sizing through launch and readout Make fast decisions trustworthy: we ship weekly and need a decision within days, but retention takes weeks to show up. You'll design the experiments and metrics that close that gap; for example, variance reduction (CUPED), sequential testing, and short-term proxy metrics validated against long-term retention and revenue Help set the experimentation standards teams rely on for Replit's highest-traffic surfaces: how metrics and guardrails are defined, and the checks that catch a broken test before it misleads anyone Use quasi-experimental designs (difference-in-differences, synthetic control, regression discontinuity) where randomization isn't feasible, such as pricing changes and regional launches Help define the data science behind an emerging personalization and recommendations workstream: problem framing, offline and online evaluation, and measuring incremental lift Model the economics of a freemium, usage-based product: credit consumption, conversion, and how pricing and limits change behavior Develop user and project segmentation from behavioral and content signals (e.g., embeddings and clustering) so growth analysis reflects what people are actually building P

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position and you must be located in Sunnyvale, San Francisco, or Seattle. You're excited about this opportunity because you will... Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because... 5+ years of professional experience 3+ years experience working in data engineering, business intelligence, or a similar role Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms Excellent communication skills and experience working with technical and non-tec

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Software Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. You're excited about this opportunity because you will… Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because… 3+ years of professional experience working in data engineering, business intelligence, or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS pl

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Role The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience in software engineering Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including

DoorDash is building the world's most reliable on-demand, logistics engine for delivery! We're looking for talented engineers to help us develop a 24x7, global infrastructure system that powers DoorDash's three-sided marketplace of consumers, merchants, and dashers. About the Team Data Platform’s Data User Experience Engineering builds the products every DoorDash employee uses to answer questions with data. That portfolio includes our AI first reporting and authoring surface,Conversational analytics with AI, Semantic and Knowledge layer along with MCP and skills layer plus the full stack infrastructure that lets users and agents reach all of it. Our users span analysts, engineers, operators, and executives across DoorDash, Wolt, and Deliveroo, on a warehouse and OLAP footprint that includes Snowflake,Spark and Clickhouse. The team is a mix of engineers who have built AI & Data platforms and products at scale. About the Role You will own the full path from a question to an answer an operator can put in a deck without checking it twice. The BI reporting surfaces are converging, and deciding what that convergence looks like while someone is authoring, building a report, writing a query, asking why a number moved, or asking for the chart they were about to build by hand. You’re excited about this opportunity because you will… Ship agentic analytics features to thousands of users where a wrong number is a real business decision made badly, and accuracy is the product Build a data platform for authoring, dashboard runtime, drill-down and cross-filter semantics, scheduling and alerting, content certification and permissions, and the embedding path that puts the same components in front of external users Streaming large result sets to the browser, rendering dozens of interdependent tiles. Build the AI experience inside that platform: agent-assisted query authoring, generated charts and widgets held to the same governance as hand-built ones Evolve the semantic laye

SpyCloud is on a mission to make the internet a safer place by disrupting the criminal underground. SpyCloud’s solutions thwart cyberattacks and protect more than 4 billion accounts worldwide. Cybersecurity is an exciting, evolving space, and being at the forefront of the fight to disrupt cybercrime makes SpyCloud a special place to work. If you’re driven to align your career with a fantastic mission, look no further! This Data Engineer II role sits on the Engineering team, reporting to the Senior Director of Data Engineering. Your focus will include evolving our data platform using technologies such as Databricks and Spark, building scalable data pipelines, and serving customers through purpose-built data stores including RDS, Elasticsearch, and DynamoDB. This is a hands-on individual contributor role with ownership of complex data engineering initiatives that support the scalability, reliability, and continued evolution of SpyCloud’s data platform. What You'll Do: Design, build, and improve scalable data systems with a focus on performance, and reliability. Use Databricks and Spark to prepare, transform, and serve high-quality data to customers and downstream systems. Build, optimize, and maintain real-time and batch data pipelines using AWS technologies such as Lambda, S3, DynamoDB, ECS, EKS, and Terraform, as well as develop and maintain pipelines within the Databricks ecosystem. Identify and implement improvements to the cost and performance of data ingestion, transformation, and storage workflows. Be available for on-call support to troubleshoot and remediate data pipeline failures outside of standard business hours. Partner with Product Management, SpyCloud Labs, and Engineering teams to understand requirements and develop effective technical solutions. Evaluate and implement modern tooling for data processing, ML/AI data workflows, and observability. Contribute to architectural and technical design decisions and help implement scalable solutions align

About the Team OpenAI’s Research Data team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods through which we acquire and create data. About the Role As a Data Program Manager, Science, you will help researchers develop and execute scientific data programs, connecting OpenAI’s research priorities with relevant data, expertise and external partners. You’ll work closely with researchers to understand their needs, assess the scientific and practical value of opportunities, and develop partnerships across the scientific ecosystem. The work could range from acquiring existing datasets to shaping research collaborations. You’ll carry opportunities from initial investigation through commercial discussions, agreements, delivery and research use, exercising sound judgement around sensitive data and relationships. Our current work focuses particularly on biology and chemistry. We welcome different combinations of scientific, technical and partnership experience. This role is based in our San Francisco HQ. In this role, you will: Develop data strategies with Research. Translate research goals, model limitations and evaluation gaps into evidence needs and success criteria. Compare acquisition with internal, public and commissioned alternatives. Find distinctive sources for research. Build trusted local and international relationships across research and industry, including organisations at the scientific frontier. Assess opportunities in scientific context. Inspect samples for provenance, context, quality and completeness. Assess usefulness, involving researchers and specialists as needed. Shape partnerships with lasting scientific value. Understand partners’ ambitions and define pilots, deliverables and acceptance criteria, considering expertise, scientific contribution and continuing relationships alongside commercial terms. Lead commercial and operational execu

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Data Scientist on the Digital Experience Insights team, you'll lead high-impact analytics initiatives, turning complex data, platform, and time-series data into rigorous predictive models, causal inferences, and strategic product metrics. You'll also apply advanced statistical and quantitative research methods to some of our most complex datasets, but the core of the role is turning that analysis into decisions leadership can act on. This role sits within a fast-moving analytics organization where the specific problems shift over time, so we're looking for someone with strong research rigor who can adapt it to whatever question is in front of them. WHAT YOU'LL DO Advanced Predictive & Statistical Modeling: Develop ML models spanning predictive modeling, time-series prediction, clustering, churn reduction, anomaly detection, and recommendation systems. Quantitative Research: Apply advanced computational methods and statistical techniques, including multilevel models and Statsmodels, to massive datasets. Executive Visualization: Create executive-level visual analytics that make complex findings accessible to senior stakeholders. Stakeholder Collaboration: Partner directly with Product, Engineering, and Business leaders to translate complex analytical findings into actionable strategy. We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in complia

Apply early for priority consideration. Gallup has limited openings for this internship, and the position will be filled quickly. As a data engineering intern at Gallup, you’ll help build and modernize the data tools, infrastructure and pipelines that enable teams to work with data at scale. Alongside experienced technical leaders, you’ll put your Python and SQL skills to work on meaningful projects while learning best practices, experimenting with modern tools and seeing firsthand how strong data engineering supports better decisions. What You’ll Do During your internship, you will: Build foundational data tooling and infrastructure designed to scale as the volume and frequency of data grow Help modernize legacy data pipelines using Python, SQL and Gallup’s evolving data platform Troubleshoot data quality issues in large, imperfect datasets Apply data engineering practices to move, transform and validate data across systems Help build reliable, efficient data workflows Learn from senior technical leaders who will mentor you on engineering practices, tools and approaches Collaborate with engineers and interact directly with stakeholders to understand needs and deliver useful solutions Use AI-enabled development tools to improve the quality and efficiency of your work What You Need Enrollment in an associate, bachelor’s or graduate degree program in computer science, data engineering, information systems, statistics, math or a related field required Classroom or work experience writing SQL required, including joins, aggregations and troubleshooting query performance Classroom or work experience coding in Python for data processing, scripting or automation required Working knowledge of relational database and data modeling concepts, including schema design and dimensional or star-schema modeling, required Comfort using AI tools such as Claude, Claude Code or GitHub Copilot to support high-quality, efficient work required Understanding of ETL/ELT concepts and how data

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Data Engineer supporting Billing & Payments Engineering, you’ll join the Finance Data Engineering team and build the foundation for accurate, scalable billing and revenue data across Anthropic. You’ll work closely with Billing Engineering, Finance and Accounting, as well as Product and other partners, to turn billing and payments data into reliable metrics, reporting and insights. You’ll make sure teams have trustworthy data that scales with our growth, and you’ll lead your own projects to enable self-serve insights that help teams make data-driven decisions. Key responsibilities Partner with Billing Engineering, Finance and Accounting to understand their data and reporting needs, and translate them into technical requirements Design, build and maintain data models and pipelines in dbt that transform raw billing, usage and payments data into canonical datasets Own revenue data accuracy and reconciliation, making sure billing, usage and revenue data tie out across systems Define success metrics for billing systems, and build the data models and monitoring to track them Set data integrity standards and SLAs for timely, accurate delivery of billing and revenue data Share on-call and data operations responsibilities for Finance Data Engineering pipelines Build dashboards and self-serve data products that track core metrics and deliver insights across the company Promote best practices for dbt, data modeling and SQL Influence the Billing Engineering roadmap from a data systems perspective Build a thorough understanding of our data models and data architecture Minimum qualifications Experience as a Data Engineer, Ana