Machine Learning Scientist Jobs

About the Role OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering. What You'll Do Full-Funnel Analytics Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention. Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations. Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders. Targeting, Segmentation & Propensity Modeling Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers. Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking. Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels. Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth. Campaign Analytics & Measurement Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy. Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership. Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews. Forecasting & Planning Build high-fidelity revenue and advertiser growth models to project perfor

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As an Applied Scientist at Dialpad, you'll be an integral part of our AI team, conducting R&D to power the next generation of autonomous voice agents and delivering features for transcribed voice and chat message data in the business communications domain. We have several research themes, including developing multi

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. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Global Growth teams. You’ll play a key role in designing and shipping experiments, as well as identifying improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self-serve user funnel to ensure a consistently high-quality onboarding experience for users globally. As Data Scientists at Stripe, our mission is to ensure that company strate

About the Team The Personality & Model Behavior team, within OpenAI’s broader Personal AGI team conducts research on how to shape personalities and guide the behavior of models. We think about topics such as emotional intelligence, reasoning, and how models interact thoughtfully with users. We’re particularly interested in understanding how individual users want ChatGPT to behave, and creating personalized models that feel uniquely tailored to each user. We integrate this research into ChatGPT and other OpenAI products that are used by hundreds of millions of users. About the Role We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models, and in areas like reinforcement learning and reward modeling. An ideal candidate is passionate about product-driven research. In this role, you will: Conduct research around personalization, personality, and model behavior by leveraging and developing tools such as synthetic data, reward modeling, and reinforcement learning. Build robust evaluations and model training pipelines to facilitate our research. Innovate new post-training methods. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: Have a deep understanding of machine learning and its applications. Have prior knowledge in training and optimizing models and building evaluations. Are willing to dive into large ML codebases to debug issues. Thrive in dynamic and technically complex environments. Have a track record of delivering innovative, out-of-the-box solutions to address real-world constraints. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through o

About the Team The Proactivity Research team, within OpenAI’s broader Personal AGI team, is focused on making our models in ChatGPT and future potential products proactive in ways that are truly useful. We're laying the technical foundations for AI that can anticipate what users need in real time, adapt as their goals and preferences shift, and build a deeper, evolving understanding of the person it's helping. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models’ personalization and agentic capabilities. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. We partner closely with research and product teams across the company to realize the vision of a highly personalized, collaborative, and proactive assistant. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve the proactivity and ability of our models to further user goals. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the other research and product teams to influence the shape of technical solutions in the product You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of LLM post-training and evaluation approaches Are passionate about, or have experience thinking about, personalization and enabling users to achieve their goals Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. About OpenAI

The Music Mission enables music creators to grow, engage, and monetize their fan bases on Spotify. Central to the Music Mission's vision is the development of promotional tools for artists and label teams, powered by Spotify's deep knowledge of listener behavior. Products like Discovery Mode, Marquee, Showcase, Music Videos, and Clips help artists and their teams grow their audiences, connect with fans, and achieve their goals on Spotify. We're looking for a Data Scientist to join Discovery Mode within the Music Mission. Discovery Mode is a tool for artists and music marketers designed to help find new listeners when it matters most. With Discovery Mode, artists and labels identify songs that are a priority, and our systems use that signal to inform the algorithms that power personalized recommendations. This role sits within the ML squad that builds and operates the models behind Discovery Mode's measurement system, and you'll serve as the squad's analytical lead. In this role, you'll partner closely with product managers and ML engineers to evaluate and improve the models that power Discovery Mode. You'll tackle complex analytical problems by designing experiments, developing evaluation frameworks, and building the analytical foundations that help keep our models accurate, reliable, and impactful for artists. As part of the Product Insights team within Music Mission, you'll help shape the measurement systems behind one of Spotify's most important promotion products. What You'll Do Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact Design and execute rigorous experiments to evaluate model quality, measure outcomes, and guide model development Conduct deep-dive analyses t

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. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Local Payment Methods (LPM) engineering and product teams. You’ll play a key role in understanding, growing, and optimising our LPM business, leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experime

Build something people love Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work . The Sales Data team is responsible for supporting the entire Commercial team through data modeling, pipelining, dashboarding, experimentation, analyses, and machine learning models. Our stakeholder teams are diverse, including Financial Planners & Advisors, Business Development Representatives, our AI Voice Agent team, Revenue Operations and Commercial Systems. We are looking for a Senior Data Scientist who has strong foundations in data modeling and machine learning to lead high priority initiatives, take ownership as a decision science expert, and help shape the direction of our Commercial team and our AI Voice Agent program. Some of your projects may include: modeling sales data, creating and improving reporting for business stakeholders, exploratory data analysis to improve our sales processes, and developing and maintaining ML models. Our models are used to solve real business problems and directly impact Wealthsimple’s north star metric. Therefore, experience with supporting sales is a bonus. In this role, you will have the opportunity to: Build and maintain new data models that are accurate and reliable Work closely with a wide range of stakeholders from Data Science, Commercial Leadership, Sales Operations, Product, Design, and Engineering Define, prototype, implement and improve ML models Design experiments to test hypotheses (e.

About the Team The Integrity team is responsible for the scaled systems that help identify and respond to bad actors and harm on OpenAI’s platforms. We protect users and the wider world by developing responses to complex harms and building the harm protections needed for new product and model launches. Integrity’s work spans not only across frontier harms like biological weapons and cybersecurity, but also high severity abuses such as child safety, nation-state misuse, and violence. About the Role Protection Scientists within Integrity design, orchestrate, and mature systems of defence against usage harms enabled by OpenAI's products. We are systems thinkers that combine deep harm domain expertise with breadth across investigation, data science, machine learning, policy and operations. Our distinctive strength is understanding how these disciplines fit together and translating between them to design and build effective systems of defence. Your core hands-on technical responsibility is harm detection. You will design, build, evaluate and maintain production detection systems, drawing on investigative expertise, data and shared engineering platforms. You will develop signals, classifiers and detection systems, and improve their ability to identify harmful activity accurately as products and behaviour evolve. You will also own the strategy and cross-functional delivery of protection work for a harm area or product launch. Working closely with investigators and other domain experts, you will ground the design in a deep understanding of how the harm occurs and translate that understanding into a system of defence. You will connect detection with policy, review, interventions, enforcement and measurement, continually calibrating the system against real cases and expert judgement as it scales. You will identify what needs to be built or changed and make it happen. Success requires setting clear priorities, aligning partners, resolving dependencies and communicating evidenc

Who We Are Artefact is a leading global consulting company dedicated to accelerating the adoption of data and AI to positively impact people and organizations. We specialize in data transformation and data marketing to drive tangible business results across the entire enterprise value chain. Artefact offers the most comprehensive set of data-driven solutions per industry, built on deep data science and cutting-edge AI technologies, delivering AI projects at scale in all industry sectors. From strategy to operations, we offer an end-to-end approach and solutions: data strategy, data quality and governance, data platforms, AI Factory, data-driven customer experience and marketing ROI. Our 2000+ employees operate in 27 countries (Europe, Asia, Americas, Middle East, Africa) and we partner with 1000 clients, including some of the world's top 300 brands such as Samsung, L'Oréal and Sanofi. What You Will Be Doing: As a Data Scientist , you will lead and conduct ambitious projects aimed at transforming clients through data. Your day-to-day responsibilities will include: Leading Transformational Projects: Spearheading ambitious projects that utilize data to transform our clients’ operations and strategies. Developing Data Science Solutions: Creating innovative data science products and solutions for both clients and our internal data science team. Building Client Relationships: Collaborating closely with your Consulting counterpart to understand client needs and strengthen relationships. Upskilling the Team: Contributing to the development of our data science team by sharing knowledge, mentoring junior Data Scientists, and promoting our work within other data departments. Ensuring Quality Deliverables: Caring for team morale and ensuring that all missions are delivered to a high standard, providing feedback and support to less experienced team members. Optimising Code: Writing highly optimized code to advance Artefact’s internal toolbox and knowledge base. What You Will Lea

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview We’re hiring a Marketing Data Scientist to partner closely with Harvey’s Marketing organization and build our marketing data science function from the ground up. In this role, you’ll serve as a trusted analytical partner to Marketing, GTM, and Finance - defining how we measure marketing success, understanding what drives channel and campaign performance, and informing where and how we invest to accelerate growth. As one of the earliest Marketing data science hires, you’ll own the development of core Marketing metrics, scalable dashboards, and analytical frameworks that enable data-driven decision-making across the business. What You’ll Do Embed deeply with the Marketing organization as a trusted partner, identifying opportunities to improve performance and drive growth

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As a Research Scientist at Snorkel AI, you will bridge the gap between cutting-edge research and real-world AI systems. This is a hands-on role where you will prototype, build, and deploy innovative AI solutions—translating research breakthroughs into scalable, practical applications that solve real-world problems. Snorkel AI operates in a fast-paced, high-impact environment, where we move quickly to push the boundaries of what’s possible. We’re looking for someone who thrives on rapid iteration, solving open-ended challenges, and driving innovation from research into production. Location: San Francisco, New York City OR REMOTE Main Responsibilities Design, implement, and validate novel AI techniques for data development such as synthetic data generation, utilizing techniques such as LLM as a Judge Prototype and build end-to-end workflows, integrating research ideas into scalable systems. Write high-quality, maintainable code, ensuring robust implementation of research-driven innovations. Move fast and adapt—iterating on solutions in response to new challenges, customer needs, and emerging research. Work closely with real-world design partners, testing solutions in applied settings with measurable impact. Collaborate with research scientists, engineers, and industry partners to push forward Snorkel AI’s broader research initiatives and rapidly productionize prototypes. Preferred Qualifications Strong expertise in AI, NLP, multi-modal models, LLMs, and g

About the Team The Integrity team is responsible for the scaled systems that help identify and respond to bad actors and harm on OpenAI’s platforms. We protect users and the wider world by developing responses to complex harms and building the harm protections needed for new product and model launches. Integrity’s work spans not only across frontier harms like biological weapons and cybersecurity, but also high severity abuses such as child safety, nation-state misuse, and violence. About the Role Protection Scientists within Integrity design, orchestrate, and mature systems of defence against usage harms enabled by OpenAI's products. We are systems thinkers that combine deep harm domain expertise with breadth across investigation, data science, machine learning, policy and operations. Our distinctive strength is understanding how these disciplines fit together and translating between them to design and build effective systems of defence. Your core hands-on technical responsibility is harm detection. You will design, build, evaluate and maintain production detection systems, drawing on investigative expertise, data and shared engineering platforms. You will develop signals, classifiers and detection systems, and improve their ability to identify harmful activity accurately as products and behaviour evolve. You will also own the strategy and cross-functional delivery of protection work for a harm area or product launch. Working closely with investigators and other domain experts, you will ground the design in a deep understanding of how the harm occurs and translate that understanding into a system of defence. You will connect detection with policy, review, interventions, enforcement and measurement, continually calibrating the system against real cases and expert judgement as it scales. You will identify what needs to be built or changed and make it happen. Success requires setting clear priorities, aligning partners, resolving dependencies and communicating evidenc

About the Team The Analytics team is looking for Data Analysts and Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our logistics 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. It is NOT just about building Machine Learning models and putting them into production. 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… Be a first-class thought partner to our product, business, finance and executive teams and help them make decisions on what’s next for DoorDash Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, Python, R, or other scripting and statistical tools Produce recommendations and use statistical techniques and hypothesis testing and other experimentation techniques to validate your findings Provide insights to enable our cross-functional team to understand marketplace dynamics, user behaviours, and long-term t