Applied Data Scientist, Unit Economics Understanding

About the PositionJoin OpenAI as an Applied Data Scientist, focusing on the critical analysis of unit economics to drive sustainable growth and establish the company as a leader in impactful innovation.In this role, you will spearhead the creation of advanced causal inference and data science models aimed at predicting and quantifying customer lifetime value…

Draup, based in San Francisco, is an AI company backed by Series A investors. The team builds an intelligence platform that supports global enterprises in workforce and go-to-market planning. Draup’s platform processes massive volumes of data, including over 1 billion job descriptions and 850 million professional profiles, and draws from more than 100 labor databases. Clients include more than 250 enterprises, with five of the Fortune 10 among them. The Silicon Valley engineering group is expanding and seeks experienced data scientists who are interested in advanced AI research and product development. This small team focuses on projects with significant impact across Draup’s offerings. What you will do Build and maintain machine learning models for classification, extraction, trend analysis, and predictive scoring using large structured and unstructured datasets. Design and execute experiments and benchmarks to measure model accuracy, address bias, and validate results at scale. Apply NLP techniques such as embeddings, named entity recognition (NER), and text classification in production data pipelines. Collaborate with engineering teams to transition models from research to production, including monitoring and drift detection. Develop evaluation frameworks to assess AI-generated outputs across multiple product areas.

Role overview Coframe is looking for Applied Scientists based in the San Francisco Bay Area. This position focuses on transforming platform data into actionable insights and results. The work brings together reinforcement learning, experimentation, and systems for personalization or ranking. What you will do Build models and strategies that support customer growth with limited manual intervention Use reinforcement learning and experimentation methods to address practical challenges Convert raw data into recommendations that guide strategic choices Location This role is based in the San Francisco Bay Area.

About GranicaGranica is an innovative AI research and infrastructure firm dedicated to creating reliable, steerable representations of enterprise data.We establish trust through Crunch, a policy-driven health layer optimizing large tabular datasets for efficiency, reliability, and reversibility. Utilizing this foundation, we are developing Large Tabular Models—systems designed to learn cross-column and relational structures, delivering trustworthy answers and automation with integrated provenance and governance.Our MissionCurrent AI capabilities are hindered not only by model design but also by the inefficiencies of the data that supports it. At scale, each redundant byte, poorly organized dataset, and inefficient data pathway contributes to significant costs, latency, and energy waste.Granica’s mission is to eliminate these inefficiencies. We leverage groundbreaking research in information theory, probabilistic modeling, and distributed systems to craft self-optimizing data infrastructure: systems that continually enhance how information is represented and utilized by AI.Led by Prof. Andrea Montanari from Stanford, Granica’s Research group merges advances in information theory with learning efficiency in large-scale distributed systems. We collectively believe that the next significant leap in AI will originate from innovations in efficient systems, rather than merely larger models.Granica is at the forefront of developing a new category of structured AI models: foundational models designed to learn and reason from the relational, tabular, and structured data that drives the global economy. While many focus on unstructured text or media, we are venturing into the next frontier: systems capable of comprehending and reasoning over structured information.Your ContributionsCreate and prototype algorithms that form the core of structured AI, enhancing representation learning and efficient information modeling for enterprise and tabular data at petabyte scale.Develop adaptive learners merging statistical learning theory with systems optimization at scale, contributing to a new generation of foundational models for structured information.Design architectures that unify symbolic, relational, and neural components, enabling AI systems to reason directly over structured enterprise data.Construct cost models and optimization frameworks that enhance the efficiency of structured learning, both computationally and economically.

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.

Crunchyroll serves a global community of anime fans, connecting over 100 million people across more than 200 countries and territories. The platform offers streaming, theatrical releases, games, merchandise, and events, all centered around anime stories and characters. Role overview The Senior Applied Scientist in Recommendation and Personalization leads scientific development for Crunchyroll’s recommendation, ranking, and decisioning systems. The focus is to help fans discover and engage with anime series, movies, manga, merchandise, and games. This position collaborates with Machine Learning Engineers, Product Managers, Engineering, Marketing, and Content teams to enhance Crunchyroll’s personalized experiences. What you will do Lead research and applied science projects in personalization, covering problem definition, data exploration, model development, evaluation, experimentation, and iteration. Define what outstanding personalization looks like for Crunchyroll across app and web interfaces, email campaigns, and integrated systems for video, ecommerce, and manga. Demonstrate the impact of personalization efforts using evidence and metrics. Partner with engineering teams to bring scientific solutions into production. Reporting structure This role reports to the Director of Data Science and Machine Learning within the Center for Data and Insights. Location and schedule This position is based in Los Angeles, California, or San Francisco, CA. Crunchyroll follows a hybrid schedule, with in-office attendance required three days per week: Tuesday, Wednesday, and Thursday.

Join Demandbase as an Applied AI Scientist, where you'll have the opportunity to push the boundaries of AI technology in a dynamic and innovative environment. As a key member of our team, your role will involve developing and implementing advanced AI solutions that drive impactful business results.We're looking for a passionate individual who thrives on solving complex problems and is eager to contribute to AI advancements. You will collaborate with cross-functional teams to integrate AI models into our existing frameworks and enhance our product offerings.

SentiLink is at the forefront of delivering cutting-edge identity and risk management solutions, providing both individuals and institutions the ability to transact with assurance. We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative approach; our real-time APIs have successfully verified hundreds of millions of identities, initially focusing on the financial sector and quickly expanding into various new markets. SentiLink enjoys the support of prestigious investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We are proud to have received accolades from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and we have been featured in the Forbes Fintech 50 list every year since 2023. Notably, we made history as the first company to deploy the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.SentiLink accommodates a flexible work environment, ranging from fully remote positions to in-office roles. As a digital-first company, we emphasize collaboration across teams in the U.S. and India. We have physical locations in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., alongside offices in Gurugram (Delhi) and Bengaluru in India. For those near our offices, we encourage regular office attendance. Certain roles, such as our engineering team in India, are designed to be primarily in-office.Role Overview:As a Senior Applied ML Scientist at SentiLink, you will be instrumental in developing our core products: advanced models aimed at identifying fraudulent activities while enhancing our expanding array of financial risk solutions. Your expertise as a seasoned researcher will be essential, making you the authoritative figure in your domain. You will frequently engage in high-impact projects that necessitate a profound understanding of the field, critical analytical skills, and robust technical capabilities. Collaboration with various teams across the organization will be key as you investigate new fraud types, innovate product offerings, and conduct analyses to support our sales and marketing efforts.

Join the dynamic Analytics team at DoorDash as a Data Scientist or Senior Data Scientist, where your expertise will directly influence strategic decisions and operational improvements. You will uncover valuable insights from vast datasets, transforming them into actionable recommendations that drive company-wide initiatives. Collaborate with diverse teams in areas like Consumer & Growth, Business Operations, and Customer Experience to elevate our analytics capabilities and impact our business in meaningful ways.

SentiLink is at the forefront of revolutionizing identity verification and risk management, providing cutting-edge solutions that instill confidence in institutions and individuals alike. Our mission is to replace outdated and inefficient methods with solutions that are exponentially faster, more intelligent, and highly accurate.With rapid growth and significant traction, our real-time APIs have successfully verified hundreds of millions of identities, beginning with the financial sector and swiftly branching into diverse markets. SentiLink proudly partners with esteemed investors, including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.Recognized by major publications like TechCrunch, CNBC, Bloomberg, and Forbes, we have been featured on the Forbes Fintech 50 list every year since 2023. We made history as the first company to implement the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.At SentiLink, we offer flexible work arrangements, from fully remote to in-office options. As a digital-first organization, we foster collaboration across our teams in the U.S. and India. We have physical offices in major cities across the United States, including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago, as well as in Gurugram (Delhi) and Bengaluru in India. If you reside near one of these offices, we encourage you to spend time on-site regularly, as some roles are designed to be hybrid or in-office.

Join the dynamic team at Mozilla as a Staff Data Scientist for Firefox. In this pivotal role, you will leverage your skills in data analysis, machine learning, and statistical modeling to enhance the user experience and drive impactful decisions.As a key contributor, you will collaborate with cross-functional teams to analyze user data, build predictive models, and communicate insights that will shape the future of Firefox. If you are passionate about user privacy, open-source technology, and data-driven decision-making, we invite you to apply!

Join Our Team as a Senior Applied Scientist!At Gridware, we are on a mission to revolutionize grid management through innovative technology. Based in San Francisco, we are pioneering a cutting-edge approach known as Active Grid Response (AGR). This initiative focuses on enhancing the reliability and safety of the electrical grid by monitoring its electrical, physical, and environmental parameters. Our advanced platform leverages high-precision sensors to identify potential issues early, facilitating proactive maintenance and minimizing outages. Backed by leading climate-tech and Silicon Valley investors, we are poised to make a significant impact in the energy sector. For more insights on our work, visit www.Gridware.io.Role Overview:We are looking for a talented Senior Applied Scientist with a strong background in machine learning and digital signal processing (DSP). In this role, you will be responsible for designing sophisticated models that operate on diverse time-series sensor data within resource-constrained environments. Your work will involve developing algorithms that optimize for accuracy while adhering to strict power and memory constraints, thereby advancing Gridware’s edge intelligence capabilities. This position requires a blend of applied research, model optimization, and close collaboration with hardware and firmware teams to implement low-level solutions.

Join HeartFlow, Inc. as a Staff Data Scientist and play a crucial role in revolutionizing cardiovascular care through advanced data analytics. You will leverage your expertise in data science to develop innovative algorithms and models that will enhance our medical imaging solutions, ultimately improving patient outcomes. Collaborate with a dynamic team of professionals who are dedicated to delivering exceptional healthcare solutions.

Faire connects independent retailers and brands worldwide through a technology-driven wholesale platform. The company’s mission centers on helping local businesses thrive by using data and machine learning to bring efficiency and insight to a traditionally fragmented market. Faire’s tools make it easier for boutiques to discover products globally and strengthen their communities. Role overview The Senior Applied AI/ML Scientist - Fulfillment joins Faire’s Data team, which builds and maintains a range of algorithms powering the marketplace. This team’s work helps small retailers compete by delivering advanced machine learning solutions and actionable insights. This position focuses on logistics and fulfillment challenges. Key areas include optimizing freight costs, determining credit limits for retailers, and expanding Faire’s retailer base through improved search engine optimization and personalized landing pages. Predicting retailer lifetime value is also a core responsibility, supporting business and product decisions. What you will do Develop and refine machine learning models for logistics and freight cost optimization Design algorithms to set optimal credit limits for retailers Enhance retailer acquisition by improving SEO and personalizing landing pages Predict retailer lifetime value to guide business and product strategy Work closely with fellow AI/ML scientists, engineers, and product managers to deliver impactful projects using marketplace data Team and culture The Data team includes scientists and engineers with experience at companies such as Uber, Airbnb, Square, Facebook, and Pinterest. Faire values resourcefulness, intelligence, and a commitment to supporting local communities. Team members contribute directly to Faire’s mission, shaping the future of independent retail with advanced machine learning. Location San Francisco, CA

Company OverviewAt Echo Neurotechnologies, we are a pioneering startup in the Brain-Computer Interface (BCI) domain, committed to spearheading advancements through state-of-the-art hardware engineering and AI innovations. Our vision is to create transformative technologies that empower individuals living with disabilities, enhancing their autonomy and overall quality of life.Team CultureBecome part of a passionate and dedicated team where your expertise is valued. In our dynamic early-stage environment, you will have the chance to influence key decisions that lead to significant, long-term impacts. We prioritize continuous learning and development, encouraging cross-functional collaboration where your contributions play a crucial role in our success.Job SummaryWe are on the lookout for a skilled Applied AI Scientist to join our innovative team. The successful candidate will harness machine learning (ML) and artificial intelligence (AI) methodologies to analyze extensive datasets of time-series data and their accompanying metadata, crafting sophisticated encoding and decoding models to decode brain activity. This work will not only propel scientific advancements but also translate into impactful solutions for patients with physical disabilities.Key ResponsibilitiesDevelop models for brain data and metadata to derive insights from both existing and future datasets, establishing high-performance inference and translation pipelines.Design and implement cutting-edge transformers and other ML models to translate brain signals into control commands for digital devices.Stay abreast of the latest AI methodologies, rapidly evaluating their applicability and effectiveness through prototypical assessments with company datasets.Collaborate effectively within a small team to refine models, design the data-science platforms, and integrate ML models into our product applications.Ensure that all code, analysis pipelines, and results are versioned, well-documented, and highly interpretable for maximum reproducibility.Assist in creating documentation for our Quality Management System, specifically related to ML implementations that will be incorporated into medical products.

Join our dynamic Analytics team at DoorDash, where we are seeking an innovative Senior Lead Data Scientist to spearhead the exploration and interpretation of complex data sets. This pivotal role will help shape our global platform expansion strategies, driving informed decisions across all facets of our organization.About the TeamThe Analytics team is dedicated to leveraging advanced analytical methodologies to inform strategic initiatives and operational decisions. As a Senior Lead Data Scientist, you will play a crucial role in transforming insights into actionable strategies that contribute to DoorDash’s success.About the RoleIn this role, you will delve into intricate data analyses to tackle significant business challenges, devise and implement experiments based on your findings, and collaborate with cross-functional teams to enact meaningful operational changes. Your expertise will be crucial in enhancing our marketplace efficiencies, optimizing customer acquisition, and addressing fraud prevention among other exciting challenges.If you thrive on identifying patterns in data chaos, possess a passion for building impactful market strategies from the ground up, and have a proven track record of employing analytics to drive revenue and operational growth, we want to hear from you!Your ImpactLead and mentor a team of Data Scientists in uncovering vital business insights while also contributing as an individual expert.Shape the Product and Operations roadmap with data-driven recommendations.Engage with senior leadership to present your team's findings and address complex business challenges.Establish measurement strategies for your area, defining key performance indicators and best practices in experimental design and statistical analysis.Craft a strategic learning roadmap informed by data insights, key questions, and hypotheses.QualificationsA Master’s or Ph.D. in Mathematics, Physics, Statistics, Economics, Computer Science, or a related field.8+ years of experience in Data Science, with a focus on product analytics and operational strategies.Proficiency in statistical tools and programming languages such as Python, R, or SQL.Strong analytical mindset with a demonstrated ability to solve complex problems using data.Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.

Join Whatnot as a Data Scientist specializing in Finance, where you will leverage your analytical skills to drive data-driven decisions that influence our financial strategies. Your expertise will play a key role in interpreting complex datasets, building predictive models, and providing actionable insights that enhance our business operations.

At Descript, we are on a mission to revolutionize the way audio and video content is created. Our innovative platform has earned the trust of renowned podcasters, influencers, and prestigious organizations like BBC, ESPN, HubSpot, Shopify, and The Washington Post. With $100M in funding from top investors, including the OpenAI Startup Fund, Andreessen Horowitz, Redpoint Ventures, and Spark Capital, we are poised for tremendous growth. We are seeking a proactive and analytical Senior Marketing Data Scientist to join our dynamic Growth team. In this role, you will collaborate with the Performance Marketing team to design and implement a comprehensive measurement framework, optimize marketing performance across the entire funnel, and drive data-informed business strategies. This crucial position will enable Descript to enhance its marketing capabilities across both B2C and B2B sectors. You will leverage AI-driven analytics tools to streamline decision-making processes and deliver scalable predictive insights. This position can be performed remotely within the United States or onsite in the San Francisco Bay Area.

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.

About UsAt Koah Labs, we are pioneering the advertising network that will drive the future of AI-native products. Our mission is to empower publishers in monetization while enabling advertisers to effectively reach their target audiences, all without sacrificing speed, user experience, or privacy.We are a passionate and close-knit team based in San Francisco, boasting a wealth of experience from industry leaders such as X, Apple, Meta, and various early-stage startups. With backing from top investors, we are rapidly expanding and gaining real traction on both the publisher and advertiser fronts.Joining Koah means becoming part of something transformative from the ground up. You will have the opportunity to ship code that influences not just our company but the broader ecosystem we are building. We prioritize speed, trust, and a deep commitment to our craft.Our Technology StackInfrastructure: Terraform, AWS, LGTM (Loki, Grafana, Tempo, Mimir), Tailscale, CloudflareData Technologies: PostgreSQL, ClickHouse, Redis, Kafka, PythonCore Application: Ruby on Rails, React, TypeScriptSDKs: Flutter, React Native, Android, iOSSample ProjectsDeveloping efficient algorithms for real-time bidding systems, leveraging current pricing literature.Creating and deploying regression models that predict end conversions based on demographic, audience, and semantic data.Utilizing privacy-preserving clustering techniques to categorize conversational data, enhancing advertiser outreach.Conducting comprehensive data analysis to uncover insights that can enhance our primary ad matching system, balancing both publisher and advertiser goals.