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Scientist Analytical Research And Development Jobs

892 active opportunities · Updated for October 2026

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Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world. What you’ll do In this role, you will play a critical part in safeguarding our financial ecosystem by investigating high-risk accounts, identifying complex fraud patterns, performing post-incident analyses, and driving cross-functional improvements to scale fraud detection. Building on these core operational duties, you will leverage your fraud, abuse, or product trust experience to improve incident response capabilities across Stripe by managing the entire fraud and abuse incident response process, developing response plans, leading workstreams, and serving as incident commander to ensure timely resolution. Furthermore, you will conduct gamedays to pressure-test response processes, drive proactive improvements, and help automate response workflows using agentic approaches ensuring we neutralize threats with speed

pythonsqlgit
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S
Stripe
📍 Dublin• Full-time
1mo ago

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve technical incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world. What you’ll do You'll play a critical role in safeguarding our financial ecosystem by investigating high-risk accounts and identifying complex patterns of fraud during incidents. You will lead incident response for product abuse and fraud events, conducting deep-dive analyses to identify root causes. By collaborating cross-functionally, you will drive improvements that enhance our fraud detection and prevention strategies at scale. Your expertise will be essential in automating response processes through agentic approaches, allowing us to safeguard merchants and neutralize threats with speed and precision. Responsibilities Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped detection and signals enrichment to reduce uncertainty and accelerate

pythonsqlgit
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S
Stripe
📍 Dublin• Full-time
1mo ago

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve technical incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world. What you’ll do You'll play a critical role in safeguarding our financial ecosystem by investigating high-risk accounts and identifying complex patterns of fraud during incidents. You will lead incident response for product abuse and fraud events, conducting deep-dive analyses to identify root causes. By collaborating cross-functionally, you will drive improvements that enhance our fraud detection and prevention strategies at scale. Your expertise will be essential in automating response processes through agentic approaches, allowing us to safeguard merchants and neutralize threats with speed and precision. Responsibilities Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped detection and signals enrichment to reduce uncertainty and accelerate

pythonsqlgit
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A
Amplitude
📍 San Francisco• Full-time• From $24K/yr
15 days ago

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management ro

gitrestmachine learning
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M
Mixpanel
📍 United States• Full-time• From $273K/yr
1mo ago

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team Internal Analysis is the data team at Mixpanel — the team that turns data from every corner of the business into the decisions that shape our product and our growth. They own the full path: from raw data in source systems, through a governed warehouse, to the models, metrics, and insights leaders across the company act on. It's two complementary disciplines under one roof. Our Analytics Engineers own the data end to end — ingesting from source systems, modeling through a medallion architecture on BigQuery, and producing the trusted tables and reporting artifacts the rest of the company runs on. Our Data Scientists build on that foundation, partnering with Product to refine the user experience and with GTM to sharpen how we grow — inspecting signals, running experiments, and surfacing the insights that change what we do next. About the Role You'll lead this team — and help shape Mixpanel's data culture. We're looking for someone who can influence the organization to become more metrics-driven: establishing clear KPIs, helping teams define success upfront, and ensuring analytics and data science are engaged as strategic partners from the start of an initiative, not brought in at the end to validate decisions already made. As we grow the data organization's remit across the company, this role has the scope to establish practices that don't yet exist, KPI ownership, cross-functional operating rhythms, a shared standard for what 'data-driven' means here, and where AI belongs in both how the team works and what the platform delivers. It takes building real trust with cross-functional leaders to

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Who is Artefact? Artefact is a next-generation strategy and data consulting firm dedicated to transforming organisations through data and AI. We combine the rigour of top-tier strategy consulting with deep expertise in data, digital and analytics to help clients achieve tangible business impact. With 2,500+ consultants, data scientists and engineers, we work with global leaders such as Samsung, L’Oréal, Orange and Sanofi. Our Swiss offices are at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design. Main Responsibilities As a Senior Consultant in our Zurich/Lausanne office, you will work at the intersection of strategy consulting and data and AI delivery. You will: Strategy Development: Work with client leadership teams to address high-stakes questions. How can AI reshape our business model? How should we govern and organise for data? Which strategic programmes deliver the most impact? Structured Problem-Solving: Break complex challenges down into decisions a client can act on, combining consulting rigour with a working knowledge of what current AI can and cannot actually do. Solution Design: Turn a business question into a solution shape — what data it depends on, what kind of platform or product it should sit on, and what “good” looks like once it is built. You will do this alongside our data scientists and engineers. Project Delivery: Support engagements end to end, from hypothesis framing and market and competitor analysis through to data maturity assessments, client workshops, governance design and implementation roadmaps. Client Engagement: Work closely with C-level stakeholders and business unit leaders. You will build trusted relationships, communicate recommendations with clarity, and keep the work aligned to what the client is actually trying to decide. Knowledge & Practice Building: Contribute to the growth of Arte

gitmachine learningai
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Brex
📍 Sao Paulo• Full-time
15 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers. What You’ll Do As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a

pythonsqlai
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Brex
📍 San Francisco• Full-time• $120.8K – $151K/yr
15 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers. What You’ll Do As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a

pythonsqlai
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PE
Private Employer
📍 Bengaluru• Full-time
1mo ago

About Us: Paytm is India’s leading mobile payments and financial services distribution company. A pioneer of the mobile QR payments revolution, Paytm builds technology that enables small businesses and consumers to participate in the digital economy. Our mission is to serve half a billion Indians and bring them into the mainstream economy through technology. About the Team: The Credit Risk Product Team is at the core of our lending operations, ensuring that our risk assessment models are efficient, scalable, and compliant with regulatory frameworks. The team collaborates closely with data scientists, engineers, and business stakeholders to develop and enhance credit risk models, decisioning frameworks, and risk mitigation strategies. By leveraging advanced analytics and machine learning, the team continuously refines underwriting processes to optimize loan performance and reduce defaults. About the Role: We are seeking a detail-oriented Credit Analyst to join our risk management team. The ideal candidate will be responsible for implementing credit risk policies, optimizing risk policies, and ensuring compliance with regulatory requirements. You will work closely with data scientists, product managers, and credit teams to enhance our underwriting models and decisioning frameworks. Key Responsibilities: * Analyze credit risk across various products, including merchant and personal loans, postpaid. * Liaison with the business team to understand the credit risk policies and implement the same on platform. * Implement the credit risk policies on our proprietary platform. * Monitor performance of credit risk policies. Share feedback with product and Policy team what's working well and what needs improvement. * Utilize alternative data sources, machine learning models, and traditional credit assessment techniques to enhance risk evaluation. * Conduct testing and scenario analysis to measure policy resilience. * Monitor key risk indicators (KRIs) and provide actionable

pythonsqlgit
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At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability. Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers. Responsibilities Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions Continuously evolve data models and schemas to meet business and engineering requirements Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform han

pythonsqlpostgresql
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PE
1mo ago

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Role: We are seeking a highly skilled Full Stack Engineer to design, develop, and scale next-generation Data Quality and AI-enabled platforms. In this role, you will work across the entire technology stack—from intuitive user experiences and data visualizations to cloud-native backend services and data processing pipelines. You will partner closely with Data Quality SMEs, Data Engineers, Product Managers, Data Scientists, and Platform Teams to build solutions that support data observability, analytics, data governance, and AI-driven insights. You will help build the next generation of D&B's Data Quality Insights platform, enabling data governance, observability, analytics, and AI-powered decision support for enterprise data products.

aigorust
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F
Figma
📍 Ca New York• Full-time• From $153K/yr
1mo ago

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The Data Platform team at Figma builds and operates the foundational systems that power analytics, AI/ML, and data-driven decision-making across the company. We serve a diverse set of stakeholders, including AI researchers, machine learning engineers, data scientists, product engineers, and business teams that rely on data for insights and strategy. Our team owns and scales critical platforms such as the Snowflake data warehouse, ML Datalake, orchestration and pipeline infrastructure, and large-scale data ingestion and processing systems, managing all data flowing into and out of these platforms. Despite being a small team, we take on high-scale, high-impact challenges. In the coming years, we're focused on building the data infrastructure layer for Figma's AI-powered products, driving cost and performance optimizations across our data stack, scaling our ingestion and reverse ETL capabilities for new product use cases, and strengthening data quality, reliability, and compliance at every layer. If you're passionate about building scalable, high-performance data platforms that empower teams across Figma, we'd love to hear from you! This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Design and build large-scale distributed data systems that power analytics, AI/ML, and business intelligence across Figma. Develop batch and streaming solutions to ensure data is reliable, efficient, and scalable across the company. Manage and evo

pythonsqlaws
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S
1mo ago

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll design, build, and own the scalable data infrastructure that powers analytics and reporting across the company. Day to day, you'll translate complex business requirements into reliable data models, own end-to-end pipeline development from raw data ingestion to clean, consumption-ready datasets, and work with leaders to prioritize the highest-impact data investments. You'll go beyond building dashboards—you'll architect the data layer that makes self-service analytics possible and deliver actionable business recommendations through rigorous analysis and data storytelling. Responsibilities Design, build, and maintain scalable data pipelines and ETL/ELT workflows that power production-grade financial reporting, risk measurement, and operational decisioning for Treasury Finance Leverage AI tools (code assistants, L

pythonreactsql
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PE
Private Employer
📍 Bangalore, Karnataka• Full-time
1mo ago

Location - Bangalore About the Team : The Platform Product team at Meesho is the backbone of our product ecosystem, empowering functions across product, business, analytics, tech, and data science. By building scalable platforms and tools, we enable teams to make data-driven decisions, accelerate development cycles, and enhance productivity. Our key focus areas include Data Acquisition, Analytics Tools, Experimentation, Segmentation, Payouts, Security, Reporting and so on, which support critical functions of Meesho About the Role : As a Platform Product Manager, you will own and drive one or more product charters within the Platform Product charter. Your role will be pivotal in enabling Meesho’s growth by ensuring seamless cross-functional collaboration and delivering impactful technical solutions. You will work closely with product managers, engineers, analysts, and data scientists across the organisation to turn complex ideas into actionable products.We’re looking for strategic thinkers passionate about building platforms that solve large-scale challenges. We want to hear from you if you are a self-starter, excel in driving initiatives independently, and thrive in dynamic environments.

C
11 days ago

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Designs, builds, and maintains large-scale data infrastructure and data processing systems. Implements robust and scalable solutions to support data-driven applications, analytics, and business intelligence. What you will do Ensures seamless integration of data from different sources, such as databases, application programming interfaces (APIs), or streaming platforms. Optimizes data processing and query performance by fine-tuning data pipelines, database configurations, and data partitioning strategies. Establishes data quality checks and validations to identify and resolve data issues, ensuring high-quality and reliable data for downstream applications and analytics. Implements security measures to protect sensitive data throughout the data lifecycle by working closely with security teams to ensure data encryption, access controls, and compliance with data protection regulations. Collaborates with cross-functional teams, including data scientists, analysts, software engineers, and business stakeholders. Designs and develops data infrastructure, including data warehouses, data lakes, and data pipelines. Establishes auditing and monitoring mechanisms to track data access and maintain data governance standards. Establishes monitoring and alerting mechanisms

pythonsqlgcp
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