Join Lyft as a Data Scientist specializing in Machine Learning, Pricing, and Rider Engagement. In this role, you will leverage your expertise in data analysis to improve pricing strategies and enhance rider experiences. Collaborate with cross-functional teams to design, implement, and optimize machine learning models that drive decision-making and business growth.

Join our dynamic team at Jobs for Humanity as a Machine Learning Data Scientist, where you will harness the power of data to drive innovative solutions for underserved communities. Your expertise will play a crucial role in developing algorithms and models that enhance accessibility and improve lives.As a key member of our team, you will collaborate with cross-functional teams to identify opportunities for leveraging data to create impactful products. If you are passionate about using your data science skills for a greater good, we want to hear from you!

Join our dynamic team at Laurel as a Senior Machine Learning Data Scientist specializing in Analytics. In this pivotal role, you will leverage your expertise in machine learning and data analysis to drive innovative solutions that enhance our decision-making processes. You will collaborate with cross-functional teams to design and implement predictive models, analyze complex datasets, and translate insights into actionable strategies.Your contributions will be key in shaping the future of our analytics framework, enabling us to better serve our clients and stakeholders. If you’re passionate about data science and eager to make a significant impact, we want to hear from you!

Join Hilbert, a pioneering data science-driven growth engine that empowers B2C teams with predictive insights into user behaviors, revenue drivers, and sustainable growth strategies. Our innovative approach compresses lengthy decision-making processes into mere minutes.Trusted by Fortune 10 enterprises and beloved brands like FreshDirect, Blank Street, and Levain Bakery, Hilbert is the backbone of their growth strategies. We are also collaborating with leading AI companies to push the boundaries of what’s possible.We are seeking a talented Data Scientist who possesses a deep understanding of B2C business challenges, develops actionable models using real-world data, and delivers impactful analyses that facilitate significant growth outcomes — all with the initiative and urgency typical of a founder.This is not a role where you simply receive tasks; you will take ownership of problems from start to finish — from problem framing and modeling to measuring impact — for enterprise clients where the stakes are high and feedback is rapid. If you understand the nuances of churn analysis for different sectors, can create effective recommendation systems from sparse data, and can clearly communicate your causal analysis to clients, we want to meet you.ROLE OVERVIEWYou will closely collaborate with the founding team, engineering, product, and go-to-market teams to enhance the data science systems integral to Hilbert. Daily responsibilities include building models, conducting experiments, analyzing data, and producing analyses that influence key decisions. Our focus is B2C, and the challenges we tackle — such as demand forecasting, customer lifecycle management, personalization, and activation — require an individual who can translate business contexts into effective modeling choices. You will thrive in a high-autonomy, high-ambiguity environment where data is often messy, incomplete, or scarce.Key Responsibilities:Develop ML models that enhance core product features: recommendation systems, search relevance, customer segmentation, demand forecasting, and activation optimization.Contribute to configurable, multi-tenant model architectures that adapt to various customer contexts and business needs, avoiding the need for custom solutions for each case.Build effective models using available data — leveraging limited, noisy, or sparse datasets while determining the appropriate level of complexity.Design and implement rigorous A/B tests and recognize when causal inference methods are necessary.

Join Hilberts as a Machine Learning Engineer / Data Scientist in our San Francisco office, where you will leverage cutting-edge technology to drive enterprise-level solutions. You will work collaboratively with cross-functional teams to design, develop, and implement machine learning models that enhance our data-driven decision-making processes.

About Pinterest:Pinterest serves as a creative haven for millions globally, offering a platform where users can explore innovative ideas, envision new possibilities, and curate unforgettable memories. Our mission is to inspire individuals to craft a fulfilling life, and this journey begins with our talented team behind the scenes.Embark on a career that fuels innovation for millions, transforms passion into growth prospects, celebrates diverse experiences, and embraces flexibility for optimal performance. Crafting a career you love? It's within reach.We are seeking a Senior Staff Data Scientist for our Engagement Ecosystem team. In this pivotal role, you will influence the development of both consumer-facing and business-oriented products at Pinterest. Your proficiency in quantitative modeling, experimentation, and algorithms will be crucial in addressing some of the most challenging engineering obstacles we face. Collaborating with a diverse array of cross-functional teams—including Product, Engineering, Design, Research, and Analytics—you will elevate our product development efforts, ensuring a scientific approach in delivering impactful solutions to our vast audience of pinners, creators, advertisers, and merchants worldwide.

Employee Applicant Privacy Notice SoFi is a national bank and financial services company that creates mobile-first tools to help people manage their money and reach their financial goals. The team values direct impact and aims to make a positive difference for members. Role overview The Senior Marketing Data Scientist - Machine Learning joins the Marketing Data Science team in San Francisco, CA. This position supports SoFi’s Marketing organization through analytics, model building, experimentation, and performance measurement to help drive marketing and growth initiatives. Work centers on designing, building, and scaling machine learning models that improve customer acquisition, conversion, retention, and lifetime value across SoFi’s products. The role draws on behavioral, transactional, and credit data to create predictive models and actionable insights. Collaboration with cross-functional teams is key for identifying business needs, managing model development end-to-end, implementing models in production, and monitoring their ongoing performance. Regulatory compliance is a consistent focus. Main responsibilities Design, develop, and deploy machine learning models to optimize customer acquisition, onboarding, and engagement for products such as loans, credit cards, investments, and cryptocurrency. Build predictive models for outcomes including customer lifetime value, conversion rates, cross-sell and upsell effectiveness, and retention across channels like email, direct mail, in-app, and Operations. Work with structured and unstructured data, such as behavioral signals, transaction data, and credit attributes, to enable audience segmentation and large-scale personalization. Maintain a feature store to streamline model development. Set up A/B testing frameworks to evaluate marketing strategies and measure their impact.

Join Our Mission to Empower Others: We’re Hiring! At GoFundMe, we pride ourselves on being the world’s largest platform dedicated to social good, connecting individuals and nonprofits to foster a supportive community. Since our inception in 2010, our collective efforts have raised over $40 billion to help people in need. We are committed to making it easy and secure for anyone to seek assistance and support meaningful causes. We are currently seeking a talented Staff Data Scientist specializing in Pricing to take the lead as a senior individual contributor. You will spearhead the scientific methods, strategic initiatives, experimentation, and AI implementation that drive pricing and yield optimization at GoFundMe. This pivotal role combines elements of economics, behavioral science, experimentation, and machine learning, directly influencing donation conversion rates, donation amounts, and overall donor experiences across our platform. Please note, candidates must be located in the San Francisco Bay Area, as this position requires in-office attendance three times a week. Your Role: End-to-End Ownership of Donation Pricing: Develop and implement analytical strategies, modeling frameworks, and key success metrics for pricing recommendations, balancing conversion rates, donation sizes, and long-term donor trust. Modeling Human Behavior: Utilize economic theories, behavioral science, and machine learning techniques to comprehend donor decision-making processes, assess elasticity, and forecast responses to alterations in product design. Leveraging Behavioral Signals: Analyze non-transactional behavioral signals (such as navigation patterns, hesitations, context, device usage, and timing) to identify shifts in intent and interaction patterns beyond direct transactions. Creating Adaptive Systems: Engineer models that evolve over time, integrating experimentation signals, feedback loops, and reinforcement learning concepts as needed. Leading Experimentation and Causal Learning: Collaborate with Product and Engineering teams to establish robust experimentation and measurement frameworks, ensuring that pricing and donation models maintain causal integrity and are safe for large-scale deployment. Incorporating External Data: Enhance behavioral models using external datasets (including macroeconomic indicators, seasonal trends, and regional signals) to gain deeper insights into donor behavior. Translating Insights into Action: Transform complex economic and behavioral analyses into actionable, deployable models.

Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through advanced cell rejuvenation techniques aimed at reversing diseases, injuries, and age-related disabilities.For more information, please visit our website at altoslabs.com.Our ValueWe embrace a singular value at Altos: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe recognize that diverse perspectives are vital to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders collaborate from around the globe, united by a common mission. Our commitment to fostering a sense of belonging ensures that every employee feels valued for their unique insights. We all share the responsibility of maintaining a diverse and inclusive workplace.What You Will Contribute To AltosAs a Senior or Principal Machine Learning Scientist, you will be pivotal in developing groundbreaking generative AI/ML models that address multi-modal, multiscale biological challenges—from virtual cell simulations to agentic target assessments. We seek an innovative, hands-on individual who thrives in a collaborative and fast-paced environment, emphasizing teamwork, transparency, scientific excellence, originality, rigor, and integrity.

About FaireFaire is a dynamic online wholesale marketplace dedicated to empowering local businesses. We believe in a future where independent retailers can thrive and compete against retail giants like Walmart and Amazon. By harnessing technology, data, and machine learning, we connect a vibrant community of entrepreneurs globally. Imagine helping your favorite local boutique source outstanding products from around the world to enhance their offerings. Our mission is to provide the tools and insights that enable small businesses to succeed in a competitive landscape.By championing the growth of independent businesses, Faire fosters positive economic impacts within communities worldwide. We are on the lookout for intelligent, resourceful, and passionate individuals to join our team as we drive the shop local movement. If you share our commitment to community, we invite you to be part of ours.About this roleAt Faire, we leverage advanced machine learning and data insights to transform the wholesale industry, enabling local retailers to stand strong against larger competitors. The Data Science team is pivotal in developing and sustaining a variety of algorithms and models that enhance our marketplace. We focus on creating innovative machine learning models that empower our customers to succeed.As a member of the Brand Data Science team focused on Listing Quality, your role will involve enhancing the quality of product listings, enabling retailers to effectively discover and assess products on Faire. You will apply ML and AI to address key challenges, including improving image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. Utilizing deep learning, multi-modal LLMs, and a human-in-the-loop approach, you'll deliver high-performance solutions. In this rapidly evolving domain, you will be at the forefront of applying cutting-edge technology to drive tangible outcomes. You will independently design and implement solutions while collaborating with the cross-functional Listing Quality pod, which includes product, design, engineering, analytics, and operations, to tackle challenges comprehensively.

Join Us in Building a Safer World.At TRM Labs, we are dedicated to providing cutting-edge blockchain analytics and AI solutions that empower law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in the fight against crypto-related fraud and financial crime. Our advanced platforms enable clients to trace the origins and destinations of funds, identify illicit activities, build robust cases, and gain a comprehensive view of potential threats. Trusted by leading agencies and businesses globally, TRM is committed to fostering a safer and more secure world for everyone.We are currently seeking a Full Stack Data Scientist to join our dynamic Knowledge Layer team. This innovative group specializes in extracting, structuring, and analyzing knowledge from vast, unstructured datasets. Positioned at the crossroads of knowledge graphs, entity resolution, graph extraction, and graph analytics, this team plays a pivotal role in enhancing TRM’s core intelligence products.While our team boasts strong backend and graph engineering expertise, we are in search of a candidate who can serve as the voice of machine learning and data science within the team. This individual will bring practical expertise in knowledge extraction and graph-based machine learning to help accelerate and scale our capabilities. This role is perfect for someone who thrives in an end-to-end operational environment, managing everything from model selection and experimentation to the productionization of ML systems and APIs.Your Impact:Design, build, and productionize machine learning models centered on:Knowledge extraction from unstructured data (e.g., Named Entity Recognition, entity linking)Graph-based learning and inferenceEntity resolution and relationship discoveryEvaluate and utilize existing ML models and frameworks to effectively tackle real-world challengesCollaborate closely with backend and graph engineers to integrate ML models into production services and APIsContribute to the design and development of knowledge graphs and ontologiesConduct exploratory data analysis (EDA) to inform modeling decisions and system architectureOversee ML components from inception to deployment, including experimentation, evaluation, and iterative improvementsHelp establish best practices for applied ML within the Knowledge Layer teamQualifications:Proven experience in machine learning, particularly in knowledge extraction and graph-based methodsStrong programming skills in Python or similar languagesFamiliarity with ML frameworks and libraries (e.g., TensorFlow, PyTorch)Experience with data manipulation and analysis tools (e.g., Pandas, NumPy)Excellent communication skills and ability to collaborate effectively with cross-functional teams

About Wispr FlowAt Wispr Flow, we strive to make device interaction as seamless as conversing with a friend.Wispr Flow has revolutionized voice dictation, now preferred by users over traditional keyboards due to its unparalleled accuracy on the first attempt. Our platform is context-aware, personalized, and effective across all devices, whether desktop or mobile.By 2026, we aim to expand beyond dictation to develop native actions within an agentic framework that comprehends and responds to user needs reliably.Our diverse team comprises AI researchers, designers, growth specialists, and engineers dedicated to reimagining human-computer interaction. We value team members who prioritize open communication, exhibit a user-centric mindset, and pay meticulous attention to detail. Our collaborative environment fosters spirited discussions, truth-seeking, and tangible impact.Having achieved a remarkable 150% revenue growth quarterly for the past year, we have successfully raised $81 million from top-tier venture capitalists and renowned angel investors.

At Lyft, we are dedicated to creating connections and serving our community. We strive to foster a workplace culture where every team member feels a sense of belonging and can flourish. The Pricing team is pivotal to Lyft’s marketplace, responsible for setting prices for all rideshare services and spearheading new initiatives. The Dynamic Pricing & Offer Selection team focuses on determining optimal prices and ETAs in real-time, balancing supply and demand within our dual-sided marketplace to enhance both immediate and long-term customer conversion and retention. As an Applied Scientist with expertise in Machine Learning and Operations Research, you will create mathematical models and deploy algorithms that inform crucial pricing and ETA decisions. Your role will involve developing ML and optimization models and implementing scalable pipelines capable of handling millions of requests daily while addressing significant business challenges impacting marketplace dynamics and rider satisfaction. You will engage with a diverse range of real-world issues across optimization, prediction, machine learning, and inference, collaborating closely with colleagues and stakeholders across Pricing, including Product Managers, Engineers, and Analysts. We seek a candidate who thrives in a fast-paced, innovative environment and excels at balancing complexity with efficiency to transform real-world business challenges into dependable solutions, systems, and decision-making frameworks.

SentiLink is at the forefront of transforming identity verification and risk management, enabling both institutions and individuals to conduct transactions with confidence. We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our rapid growth reflects the significant traction we've garnered, with our real-time APIs successfully verifying hundreds of millions of identities, especially within the financial services sector, while swiftly expanding into other markets. SentiLink enjoys the backing of top-tier investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We have received accolades from major publications including TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and have consistently ranked on the Forbes Fintech 50 list since 2023. Notably, we made history by being the first company to implement the eCBSV and provided testimony before the United States House of Representatives regarding the future of identity verification.SentiLink promotes a flexible working environment, offering various work arrangements ranging from fully remote to in-office. As a digital-first organization, we emphasize strong collaboration across teams in the U.S. and India. Our offices are located in cities including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram (Delhi) and Bengaluru in India. If you are near any of these locations, we encourage regular in-office engagement. Some positions are designed to be hybrid or in-office. For instance, our engineering team in India primarily operates from our Gurugram office.

Okta secures digital identity for both AI and human users, building infrastructure that helps organizations adapt to new challenges. The company focuses on solving complex problems that have a real impact for its customers. The Pricing Strategy team partners with Product, Finance, Sales, and Operations to define how Okta packages, prices, and monetizes its products worldwide. This group blends strategy with analytics, using market trends and customer data to develop recommendations that influence executive decisions and field execution. Role overview The Principal Data Scientist, Pricing Strategy, reports to the Head of Pricing Strategy. This position leads analytics projects that shape pricing and packaging strategies across Okta’s product portfolio. The role combines quantitative analysis with strategic thinking, developing measurement methods, building and deploying models, and running test-and-learn programs to guide monetization. Collaboration with senior leaders in Product and Go-to-Market teams is essential, turning open-ended questions into actionable insights and scalable plans. What you will do Strategic Pricing Influence: Work with Product, Go-to-Market, and Finance leaders to shape pricing, packaging, and discount strategies using data-driven insights. Advanced Analytics and Modeling: Build and apply models and analytical frameworks to forecast pricing effects, predict customer behavior, and estimate revenue outcomes across regions and segments. Experimentation and Pilots: Design and evaluate pilots and test-and-learn initiatives for new pricing strategies, including defining success metrics and evaluation methods. Deep-Dive Insight Generation: Analyze large, complex datasets to uncover drivers of purchasing, discounting, retention, and monetization performance. Metrics and Dashboards: Develop dashboards and reports that clearly communicate findings to stakeholders. Location This position is based in Bellevue, Washington or San Francisco, California.

At Causal Labs, we are on a groundbreaking mission to develop general causal intelligence—artificial intelligence that not only predicts future events but also determines the most effective actions to influence those outcomes.To achieve this monumental goal, we are constructing a Large Physics Foundation Model (LPM). Our focus is on domains governed by physical laws, which inherently exhibit cause-and-effect relationships, setting them apart from traditional visual or textual data.Weather serves as the ideal training environment for our LPM, being one of the most extensively observed physical systems available. It provides immediate, objective feedback from sensory observations and boasts data scales significantly larger than those currently employed to train existing language models.Our team at Causal Labs includes leading researchers and engineers with backgrounds in self-driving technology, drug discovery, and robotics, hailing from prestigious organizations such as Google DeepMind, Cruise, Waymo, Meta, Nabla Bio, and Apple. We firmly believe that achieving general causal intelligence will represent one of the most critical technological advancements for our civilization.We are seeking innovative researchers eager to confront unsolved challenges in the field.This role presents an opportunity to create powerful models rooted in observable feedback and verifiable ground truths. If you possess experience in pioneering research and training large-scale models from the ground up in areas such as language and vision models, robotics, or biology, we invite you to join our mission.

Join Arena Intelligence as a Machine Learning ScientistAt Arena Intelligence, we are revolutionizing how AI models are evaluated in real-world scenarios. Founded by innovative researchers from UC Berkeley’s SkyLab, our mission is to push the boundaries of AI evaluation and ensure its practical application.With millions of users engaging with our platform each month, we prioritize community feedback to develop transparent, rigorous, and human-centered model evaluations. Our leaderboards serve as the benchmark for AI performance, gaining the trust of leading enterprises and AI labs to understand the reliability, alignment, and impact of AI systems.Our diverse team comprises experts from esteemed institutions such as UC Berkeley, Google, Stanford, DeepMind, and Discord. We foster a culture that values truth, agility, craftsmanship, curiosity, and impact over hierarchy. We are committed to creating an environment where talented individuals from all backgrounds can excel in their work.Role OverviewWe are seeking a passionate Machine Learning Scientist to spearhead our open-source research initiatives, including the development of open datasets and code releases. You will be instrumental in advancing how AI models are evaluated and understood globally.In this position, you will operationalize our dedication to openness by curating impactful datasets, developing innovative methodologies, and establishing reproducible benchmarks. Your contributions will enhance our public leaderboards, empower community tools, and promote transparency in AI evaluation on a global scale.This interdisciplinary role involves collaboration with engineers, product teams, marketing, and the broader research community to refine model comparisons, analyze preference data, and explore dimensions like style, reasoning, and robustness. You will also work closely with our go-to-market teams to advocate for our open research initiatives, strengthen research partnerships, and encourage community engagement.If you are excited by complex challenges, rigorous evaluation processes, and scientific outreach, we invite you to apply!

Founded in 2007, Airbnb has transformed the travel landscape, growing from a humble start with three guests to a vibrant community of over 5 million hosts welcoming more than 2 billion guests worldwide. Every day, our hosts offer distinct stays and experiences, fostering authentic connections between travelers and local communities.Join Our Collaborative Team:You will be part of a dynamic group of data scientists, analysts, engineers, product managers, and designers dedicated to developing innovative pricing solutions for Airbnb hosts. Your primary team will include data scientists within the Guest & Host Data Science organization, who create models, essential tools, and insights to enhance the Airbnb marketplace for both guests and hosts. Your Impactful Contributions:Play a crucial role in shaping a pricing guidance system for our hosts and employ various methods (both experimental and observational) to evaluate the effectiveness of pricing feature launches. You will spearhead innovative pricing science initiatives, including pioneering 0-to-1 projects that require a blend of scientific rigor and creative business insights. Your most impactful work will involve:Working closely with product and cross-functional teams to develop and implement pricing strategies and guidance for hosts, translating sophisticated modeling into practical recommendations.Creating foundational models and experimental frameworks that balance marketplace supply and demand, using empirical methods to evaluate and enhance pricing feature impacts.Crafting engaging data narratives to reveal actionable insights, empower data-driven decision-making, and steer the future of Airbnb’s pricing ecosystem. A Day in Your Role:Gaining a comprehensive understanding of host perspectives on pricing and their interactions with our application through analysis and research.Building strong relationships with cross-functional partners in Product, Engineering, and Analytics.Coding in Python, SQL, and R to model, simulate, and measure the impact of new pricing features.Diving into data creatively to assess the varying effects of pricing feature launches, converting these insights into clear recommendations.Sharing findings and insights with leadership and partners in a straightforward and impactful manner.

Join Handshake as a Machine Learning Research Scientist and contribute to groundbreaking projects that leverage advanced algorithms and data analysis to drive innovation. In this role, you will collaborate with a dynamic team to design, implement, and evaluate machine learning models that enhance our products and services. Your expertise will be pivotal in unlocking new insights from data, improving user experiences, and shaping the future of our technology.