Data Analyst Jobs

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 . As a Senior Data Scientist on the CX Consumer Analytics team, you will serve as the foundational link between CX operations and top-line financial impact, owning the revenue calibration models, experimentation frameworks, and behavioral intelligence that connect every customer support interaction to Coinbase's asset accumulation flywheel. You will partner closely with CX Analytics Engineers, Program Managers, and Product teams to translate complex operational and behavioral data into defensible, executive-ready insights that drive measurable improvements in retention, product adoption, and automation quality. What you'll do: Own and evolve CX's Downstream Impact of Support (DSI) revenue calibration models, translating support interaction data into quantified revenue signals. Design and execute causal inference frameworks and experiments to measure the incremental impact of CX programs (Concierge, Proactive Outreach, automation interventions) on customer retention and product engagement. Build and maintain LLM-powered classification pipelines for CX contact taxonomy, customer friction detection, and issue attribution, partnering with Analytics Engineers to productionize models into CX's governed Source of Truth infrastructure. Partner with CX Program Managers and Product teams to define segmentation models and behavioral signals that enable personalized experiences an

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

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Talent Management & Analytics team is scaling to its next major milestone—integrating advanced predictive insights and tactical AI into our workforce systems. Our mission is to build the data solutions that help the entire company recruit exceptional talent, design high-performing team structures, and put active organizational insights directly into the hands of everyone making team decisions. Operating at the intersection of data science, product development, and organizational psychology, we are transforming how Robinhood uses data to empower our workforce and anticipate organizational needs. As a Staff Data Scientist, you will serve as the team's technical and strategic anchor, owning the vision, design, and delivery of the high-impact data products that our executives, people partners, and line managers rely on every day. Your focus will be entirely on solving meaningful organizational problems: understanding what enables exceptional talent to thrive, accelerating team performance, and designing proactive strategies that support long-term retention across Robinhood. This is a unique opportunity to apply state-of-the-art language models and predictive analytics to

Senior Manager, AI, Data, Analytics & Reporting Product Area Lead — Greece - Thessaloniki Pylaia. Apply via Workday.

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leading orchestration platform for the autonomous enterprise, driving business transformation at the lowest total cost of ownership. Redwood empowers organizations to intelligently automate and orchestrate mission-critical business and IT processes across complex ERP, hybrid cloud, data and emerging agentic AI systems. Through its SaaS-first automation fabric—with AI embedded across the automation lifecycle—Redwood accelerates the path to autonomous operations. Backed by 30 years of experience and trusted by more than 50% of the Fortune 50, Redwood helps organizations unlock human potential to focus on innovation, growth and what’s next. CORE VALUES One Team. One Redwood Make Your Own Weather Obsess over Customer Success Work the Problem Be Curious Own the Outcome Respect Each Other YOUR IMPACT We’re looking for a Marketing Analytics Manager who will own the strategy and optimization of marketing performance reporting across the organization. This role goes beyond dashboard creation—you’ll act as a strategic partner to marketing and leadership, translating data into actionable insights that drive pipeline growth and improve campaign performance. You will define how success is measured across the marketing funnel, proactively identify trends and opportunities, and ensure the organization has a clear, consistent view of performance. You will partner closely with Marketing, RevOps, and data teams to enable scalable analytics solutions and trusted reporting. Analytics Strategy & Ownership Own the end-to-end marketing analytics strategy, including defining KPIs, establishing reporting frameworks, and standardizing measurement approaches across the funnel Establish and govern a consistent source of truth for marketing performance across channels, segments, and funnel stages Define success metrics tied to pipe

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors The Analytics Engineering team at Nextdoor transforms diverse data sources into solutions for business challenges. As a lean yet impactful team, we cover the entirety of the Nextdoor business and excel in cross-functional collaboration to empower company-wide data-driven decision-making. By amplifying the voices of our platform's users, we play a pivotal role in building stronger, healthier communities. We’re at an exciting transition, evolving from a traditional Business Intelligence focus to a broader mandate that includes strengthening data foundations and developing data products, such as analytics self-serve, for all Nextdoor data consumers. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Analytics Engineering Manager , you will Develop and own the vision for Analytics Engineering, delivering curated datasets, dashboards, and

Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . As an Analytical Engineering Manager, you lead a team of Analytical Engineers who own the data foundations for the business: the Gold layer, canonical metrics, certified dashboards, and semantic layer that make Asana's most important numbers trustworthy, and that make AI-powered self-serve through Claude and Databricks Genie actually work. You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether business stakeholders trust the data in your team's domains and can answer their own questi ons without routing through your team. This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, setting a high bar for data-model quality and stakeholder trust. Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM), taking accountability for curated data models, canonical metrics, dashboards, and Genie spaces. Treat every recurring insight as a product with an owner, a cadence, and an SLA, building a catalog of trusted, versioned data products instead of one-off rebuilds. Drive self-serve enablement by prioritizing Go

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 . Senior Analytics Engineer As a Senior Analytics Engineer on the Platform team, you'll build the scalable data models and pipelines that power analytics, experimentation, and decision-making across Coinbase. Our Analytics Engineering team transforms raw data into trusted, well-modeled sources that stakeholders across Product, Engineering, and Data Science rely on daily. You'll own end-to-end data solutions for specific business domains, turning complex data flows into clean, reusable frameworks that unlock commercial value at scale. What you'll do: Own end-to-end data modeling for assigned business domains, from understanding source system data flows through designing modular, reusable models (star/snowflake schemas) that serve as the single source of truth for downstream teams. Build and optimize ETL/ELT pipelines using modern tools like dbt and Airflow, ensuring data quality, reliability, and performance at scale across Snowflake or similar warehouse architectures. Partner with Engineering, Product, and Data Science teams to identify data gaps, define requirements, and deliver data products that directly enable experimentation, ad hoc analysis, and business metric optimization. Develop scalable abstractions and frameworks (UDFs, Python packages, internal data apps) that multiply the efficiency of other data teams and reduce time-to-insight across the organization. D

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

About the Team The Analytics team is looking for Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash. About the Role Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. This is a rare operational and actionable data-driven experience. We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… As a senior Individual Contributor, mentor and influence junior Data Scientists in investigating complex issues and uncovering key drivers of our business Influence the Product and Operations roadmap by making actionable recommendations based on data Interface frequently with senior leadership to showcase your team’s work and tackle complex business problems Drive measurement strategy for the area under scope, defining success metrics and implementing best practices around experiment design and statistical analysis Develop a strategic learning roadmap based on data observations, strategic questions, and hypotheses We're excited about you because you have… A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain 8+ years of experi

About the Role As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In This Role, You Will Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected v

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

About the Team Merchant Analytics helps DoorDash make better product, business, and go-to-market decisions through high-quality analytics, predictive modeling, experimentation, and strategic thought partnership. We work across some of DoorDash’s most important merchant and marketplace priorities, building the measurement, insights, and decision frameworks that improve outcomes for merchants and drive company impact. About the Role We’re hiring two Data Science Managers, each to lead a pod within Merchant Analytics and help shape high-priority product and business decisions. In this role, you will lead a team of data scientists, partner closely with Strategy & Operations, Product, Engineering, and business leaders, and turn ambiguous questions into clear recommendations that influence roadmap and plan outcomes. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and ensuring analytics work is tightly connected to measurable business impact. You will report into Director, Data Science on our Merchant Analytics team in our Analytics organization. You’re excited about this opportunity because you will… Lead and develop a team of data scientists responsible for high-impact analytics, predictive modeling, and decision support tied to DoorDash’s most important product, business, and GTM priorities. Partner closely with Strategy & Operations, Product, Engineering, and business leaders to shape decisions, influence roadmaps, and improve plan-critical metrics. Define success metrics, build measurement frameworks and predictive models, and use experimentation and analysis to connect product and operational levers to business outcomes. Build a high-performing pod that balances analytical rigor, strong prioritization, and clear storytelling in a fast-moving environment. Scale reusable analytics frameworks, tools, models, and best practices that make the broader organization more effective over time. We’re excited