Machine Learning Scientist Jobs

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary At Micron, we are transforming the future of semiconductor manufacturing through data, artificial intelligence, and advanced analytics. As a Senior/Staff Data Scientist , you will leverage massive volumes of manufacturing, engineering, and business data to develop predictive models, uncover actionable insights, and drive intelligent decision-making across our global operations. In this role, you will collaborate with world-class engineers, data scientists, and business leaders to solve complex real-world challenges using machine learning, statistical modeling, and advanced analytics. You will have the opportunity to develop innovative AI-driven solutions that improve product quality, optimize manufacturing performance, accelerate operational excellence, and shape the future of intelligent manufacturing. If you are passionate about turning data into impactful business solutions and thrive in a highly automated, data-rich environment, we invite you to join our team and make a meaningful difference. Responsibilities Collaborate with cross-functional teams including Engineering, Manufacturing, Product, and Business stakeholders to identify opportunities for data-driven solutions and process improvements. Analyze l

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. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

We are seeking a highly skilled and experienced Data Scientist to join our Perception Verification and Validation team. The team is responsible for verifying and validating the perception stack of our autonomous driving system. The candidate will work closely with other data scientists, perception engineers, and systems engineers to develop datasets and metrics to quantify the performance of our perception system. The candidate will also help define key performance metrics that will enable perception engineers to directly measure the impact of new features on both the overall Perception stack as well as end-to-end system behavior. In this role, You will... Define key performance metrics that will help perception engineers to measure the impact of new features on the perception stack and the end-to-end system behavior Create and maintain datasets used to evaluate the perception stack and end-to-end driving performance. Analyze large scale metric results to identify patterns and insights about perception failure modes. Present results and insights to leadership. Design and implement statistical methods to quantify uncertainty in our performance and validation metrics. Qualifications Master's or PhD degree in Statistics, Mathematics, Computer Science, or a related field Proficient using data query languages (SQL and/or Spark/scala) to quickly build complex yet efficient data queries at scale and using Python to build production-quality code Basic experience with autonomous driving, safety-critical systems, or computer vision systems. Proficient in exploratory data analysis (EDA) and data visualization to understand and present trends and their implications for the business. Background in statistical modeling and analysis; including experience making data-driven decisions that connect point and uncertainty estimates to business impact. Bonus Qualificati

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the role Appier's Ad Cloud handles millions of bid requests per second, and that number keeps climbing. Behind every request is a chain of decisions: how much to bid, what to recommend, which creative to show, how fast the system responds. Each one is a lever on campaign performance, and at this scale a 1% improvement is enormous. Your job is to find those levers in the data. You will turn campaign, auction, and user-behavior data into insights about where the next performance gain is, prove it with rigorous A/B testing, and drive the change across the organization. This is not a back-office role. You will work hand-in-hand with ML scientists, engineers, product managers, and the operations team, and you are expected to set the agenda with data and push until the improvement shows up in live campaigns. AI now handles much of the mechanics: writing queries, drafting code, producing charts. What it does not do is decide which question is worth asking, notice that a number does not add up, or keep digging when the first explanation is too convenient. That is the job. We are looking for someone who is relentlessly curious about why , and who cannot leave an unexplained anomaly alone. What You Will Do Find where performance comes from. Mine campaign, bidding, and user data to identify the highest-leverage opportunities to improve online campaign performance, and turn them into testable hypotheses. Get to the root cause. When performance shifts or metrics contradict each other, dig until you understand the

About the Team At Trendyol Tech, our mission is to create a positive impact in our ecosystem by enabling commerce through technology. We solve complex problems with data, creativity, and agility — always driven by real outcomes. With a culture built on learning, collaboration, and ownership, we grow together while building what’s next. About the Role Our team builds the language intelligence and retrieval foundations behind Trendyol Search across multiple regions. We focus on helping customers express their intent accurately and discover relevant products quickly, regardless of the language or market they search in. As a Data Scientist, you will work on high-impact problems at the intersection of NLP, information retrieval, and e-commerce search. You will contribute to multi-regional search models covering spelling correction, query understanding, semantic and vector search, while taking particular ownership in improving the Arabic-language search experience. Your work will directly improve product discovery for millions of customers across Trendyol's markets. Responsibilities Develop and improve query understanding capabilities for Trendyol's search experience across multiple regions and languages, including spelling correction, query normalization, query rewriting, intent detection, and semantic retrieval. Build and evaluate vector search, embedding, and retrieval models that improve the relevance of product discovery for customers across different markets. Take a leading role in Arabic-language search initiatives, addressing language-specific challenges such as dialectal variation, orthographic normalization, transliteration, morphology, mixed-language queries, and spelling errors. Analyze large-scale structured and unstructured data, including search queries, product content, user interactions, and linguistic signals across the Trendyol ecosystem. Design robust offline evaluation methodologies and quality metrics for

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: The Data Analytics and Transformation team encompasses the Data Engineering, Semantics, Data Science, Strategic Intelligence and Business Transformation functions. The team provides analytic support and a strategic perspective to the different functions within Celonis to enable them to make evidence-based decisions. We deliver actionable insights by collecting, organizing and interpreting data about user journeys, product telemetry, incidents, infrastructure utilization, sales motions, and much more. We transform data into analytic assets by conducting exploratory analysis, identifying outliers, validating hypotheses, building statistical models, quantifying risk; communicating findings through well crafted stories and critical recommendations. The Role: As a Data Scientist in the Data Analytics and Transformation team, you will play a key role in developing and communicating data-driven insights that will help with strategic and tactical decision making in a hyper growth environment. You will be using your analytical and data science skills to create and fine tune statistical and machine learning models, carry experimentation, build with foundation models - RAG, agents, evals and communicate findings to engineers, m

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 The Data organization develops infrastructure, statistical models, and products using financial data. Our Scientists and Engineers work together to make data —and insights derived from data — a core asset across the company. Our work is ingrained in Brex’s decision-making process, in the efficiency of our operations, in our risk management policies, and in the second-to-none experience we provide our consumers. What You’ll Do Our Data Scientists are responsible for the entire model development lifecycle, from conception with stakeholders, through model development and productionization, to following through to see that the desired business impact is achieved — including circling back with stakeholders to make product or strategic decisions. Responsibilities Drive Data & AI solutions from inception to deployment to efficiently manage risk and/or improve customer experience. Be responsible for the full machine learning

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: Open Intelligence (OI) is one of WPP’s most strategic bets - a flagship data and AI initiative at the intersection of machine learning, advertising technology, and audience insight, built to power the next generation of media intelligence. Operating across the US and UK and expanding across EMEA and APAC, OI runs at true global scale. To lead the next phase of development at the embedding and applied-AI layer of OI, we are hiring a Data Science Team Lead in Copenhagen. You will guide a small, sharp team building critical capabilities - from multimodal embedding spaces and Model Context Protocol (MCP) servers to agentic tools and UIs - that make the rest of OI’s AI ecosystem thrive. What you'll be doing: Line-manage and grow the team : Drive 1:1s, recruitment, performance, mentorship, and day-to-day technical and team direction. Own technical architecture & direction : Lead the technical vision and design for well-distributed multimodal embedding spaces (text, image, video), MCP server tooling, and user-facing chat agents + UI. Translate strategy into action : Take

How does a company with thousands of people building hundreds of products stay focused on what matters most? That's the question the Company Planning and Execution (CPE) team works on every day. We design the systems, processes, and insights that help Spotify plan, prioritise, and deliver at scale. As a Data Scientist on CPE, you'll sit at the intersection of data, strategy, and operations. You'll bring clarity to complex questions by turning operational and strategic information into clear stories, recommendations, and decision frameworks that help leaders and teams act faster and smarter. You'll also explore how AI and automation can change the way people access insights and make decisions. You'll work closely with data scientists, engineers, PMs, and business partners across the company to help refine how Spotify executes at scale. If you like making sense of ambiguity, care about how organisations work, and want your analysis to shape real decisions, this is the role. What You'll Do Formulate hypotheses related to how Spotify plans and delivers, and communicate insights effectively to a range of audiences. Apply analytical techniques — including statistical models and machine learning — to identify trends and generate insights that improve how we work. Build and maintain the data models, pipelines, and dashboards that provide visibility into how Spotify plans and executes. Develop structured narratives and recommendations — not just charts, but the "why" and "so what" — in our semi-annual Planning and Execution Insight reports and recurring briefings. Explore how AI and automation can make insights faster to produce and easier to access across the company. Who You Are Curious about how organisations work — not just the data, but the decisions and systems behind it. 5+ years of experience with a quantitative background in science, economics, engineering, or a related field. <li

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Data Analytics and AI org (DAA) is actively seeking a Staff Data Scientist, GTM to provide technical leadership for Snowflake’s next generation of AI & Machine Learning powered GTM decision systems. You will contribute to high-impact work across sales and marketing: propensity models across the GTM funnel, measuring the causal effect of GTM investments and interventions, and recommending actions for accounts, leads, opportunities, and customers. This role goes beyond developing models. You will define how decision systems are designed, evaluated, productionized, and integrated into the workflows of sellers, marketers, and business leaders. You will establish reusable technical standards, guide investment across use cases, and ensure that sophisticated methods translate into measurable business impact. What You’ll Do • Set the technical direction for a portfolio of AI & Machine Learning GTM decision systems spanning Sales and Marketing. • Develop pipeline forecasting methods that model stage progression, conversion, deal timing • Build account, lead, opportunity, and customer models that identify propensity, risk, potential, and likely next outcomes. • Develop recommendation and next-best-action systems that determine where GTM teams should focus, which action to

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 Data Scientist, Commercial Analytics will leverage advanced analytics, machine learning, experimentation, and predictive modelling to identify growth opportunities, reduce customer churn, optimize territory and account planning, and support strategic decision-making across the commercial organization. This role works with large-scale customer, sales, product usage, and financial datasets to develop scalable analytical solutions that influence key business outcomes. It aligns closely with commercial priorities such as Annual Recurring Revenue (ARR) growth, retention, expansion, customer lifetime value, sales effectiveness, and portfolio optimization. Responsibilities: Develop, deploy, and maintain machine learning models that support Customer churn prediction, Upsell and cross-sell propensity scoring, Whitespace opportunity identification, Customer lifetime value prediction, Renewal risk assessment and Sales forecasting. Apply advanced statistical techniques to identify key drivers of customer behaviour and commercial performance. Design and evaluate experiments to improve acquisition, retention, and expansion outcomes. Build analytical frameworks to improve Sales and Annual Recurring Revenue (ARR), Customer retention, Expansion revenue and Sales productivity. Conduct deep-dive analyses into customer, product, and sales performance. Create segmentation models that support territory design, account pl

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 Our Data Science team partners 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. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust. What you'll do We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business. Data scientists on this team apply supervised and unsupervised machine learning, statistical mod

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 Our Data Science team partners 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. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. The Link Data Science team at Stripe is the dedicated data science and analytics partner for Link - currently with a strong product market fit in offering one-click checkout to shoppers who shop across Stripe’s merchant network, trusted by more than 300M users. The Link team has an exciting roadmap to launch consumer-friendly features to make Link the best way to spend, while continuously generating conversion uplift to our merchants. We are hiring for two data scientists dedicated to: Local Payment Methods - We want to enable consumers across the globe to be able to pay using their preferred local payment method like UPI, PIX etc. This allows me

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 Data Scientist in the Pay, Integrity & Identity org, you will collaborate with our world class team of engineers, product managers, analysts and other data scientists to help create best in class pay platforms, stop fraudulent actors from harming our riders & drivers fraud and build user trust on the Lyft platform. You will run experiments (A/B tests) and develop data driven solutions to launch new features and remove the bad actors from the Lyft platform while maintaining a positive experience for genuine users. We’re looking for an intellectually curious individual who has extraordinary attention to detail, a track record of analytical problem-solving and skilled communication. Prior experience in the fintech, fraud or identity space is preferred. Responsibilities: Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes Partner with product managers, engineers, and operators to translate analytical insights into decisions and action Build data pipelines and develop analytical frameworks to monitor business and product performance Set business metrics that measure the health of our products, as well as passenger and driver experience Collaborate with product and engineering and communicate findings to stakeholders in a clear and concise manner Experience: Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience 4-6+ years of industry experi