Senior Applied Scientist in Recommendation and Personalization

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 (LTV). Your ability to translate complex data insights into strategic recommendations will be crucial for guiding our growth initiatives. This position demands a blend of technical expertise and executive communication skills.This opportunity is based at our San Francisco headquarters, with a flexible hybrid work model (three days in the office per week). Relocation assistance is provided.Your VisionDevelop robust causal inference and predictive analytics capabilities to assess and forecast LTV across various customer segments (B2C and B2B), and measure the incremental effects of diverse actions or product features on customer LTV.Craft customer “happy paths” by identifying optimal adoption journeys that maximize lifetime value while ensuring customers derive the full benefits from our ecosystem.Evaluate price elasticity to inform product packaging, monetization strategies, and pricing models.Your ResponsibilitiesCollaborate with cross-functional teams (Finance, Product, Data Engineering, Go-to-Market, and other Data Science teams) to develop causal inference and predictive models that influence key business decisions.Design and maintain LTV models across various product lines and customer cohorts.Create scalable frameworks and models that make economic insights accessible to leadership and functional teams.Support strategic pricing and investment decisions with thorough analytical and causal evidence.Lead cross-functional data science initiatives, ensuring analytical precision, clarity, and timely execution.Ideal Candidate ProfileExceptional executive communication skills — ability to simplify complex analyses into clear, actionable insights for leadership.Technical proficiency — expertise in ROI analysis, causal inference, statistical modeling, and ML predictive models; strong command of Python and SQL.Strategic acumen — capacity to connect analytical insights to tangible business outcomes, providing the “so what” that drives leadership decisions.

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 hiring Applied Scientists in the SF Bay Area to turn platform data into practical insights and measurable results. This role sits at the intersection of reinforcement learning, experimentation, and personalization or ranking systems. What You Will Do Develop models and strategies that help customers grow, operating with minimal human input Apply techniques from reinforcement learning and experimentation to real-world problems Translate raw data into recommendations that inform strategic decisions Location San Francisco Bay Area

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.

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.

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 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.

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.

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.

About Our TeamJoin the User Operations team at OpenAI, where we are dedicated to delivering outstanding customer experiences with our innovative products. Our team tackles complex challenges, provides expert technical guidance, and empowers customers to fully leverage our solutions. Collaborating closely with Sales, Technical Success, Product, Engineering, and other departments, we ensure a seamless experience for our diverse clientele, ranging from emerging startups to established global firms. Given the rapid pace of innovation at OpenAI, transforming our extensive support data into real-time insights and scalable analytics is vital for maintaining exceptional customer satisfaction as we move toward AGI.Role OverviewWe are looking for a proactive Support Data Scientist who will analyze user-support data to identify trends, volume patterns, and friction points, converting insights into actionable strategies and continuous reporting. You will design and maintain self-serve dashboards that provide real-time information to stakeholders, ensuring seamless collaboration with Data Science and Engineering teams for clean data pipelines, robust modeling, and scalable tools. Your work will focus on proactive friction detection and real-time service health monitoring, delivering insights that drive informed decision-making rather than just aesthetic presentations.This position is based in San Francisco, California, employing a hybrid work model with three days in the office each week. We also offer relocation assistance for new hires.Key Responsibilities:Analyze extensive support and product datasets to identify trends, key drivers, and user experience challenges, translating findings into actionable insights.Develop and maintain user-friendly self-serve dashboards and reporting tools that empower non-technical teams to address their own data inquiries.Create a standardized metrics framework for service performance, establishing automated data-sharing pipelines and scorecards with our BPO partners to maintain a unified real-time view of success.Utilize large language models (LLMs) to build custom classifiers that automatically categorize and segment incoming data, enhancing routing accuracy, enriching self-service insights, and accelerating root-cause analysis.Collaborate with Data Engineering to ensure reliable data pipelines, implement quality checks, and document processes for sustained excellence.

Join our innovative team at Pinterest as a Senior Data Scientist in the Core division. We're looking for a data-driven professional who is passionate about leveraging data analytics and machine learning to enhance user experience and drive business outcomes. At Pinterest, you will collaborate with cross-functional teams to develop data models and insights that influence strategic decisions.

About GustoAt Gusto, we are dedicated to empowering the small business economy. We take care of essential services such as payroll, health insurance, 401(k)s, and HR, allowing business owners to concentrate on their passion and serving their customers. With teams based in Denver, San Francisco, and New York, we proudly support over 400,000 small businesses nationwide, and we are committed to building a workplace that reflects and celebrates the diversity of our customers. Discover more about our Total Rewards philosophy. About the Role:We are seeking a highly skilled and motivated Staff Data Scientist with a minimum of 7 years of experience in a business environment. In this pivotal role, you will utilize experimentation, statistical inference, and causal analysis to drive strategic decision-making that enhances our organization's success. The ideal candidate is a trusted data storyteller with strong statistical and programming skills, passionate about using these abilities to support small businesses in thriving.About the Team:In this position, you will collaborate closely with our Product, Engineering, Design, Finance, and other Data teams to become an expert in your domain's data, define and track metrics that provide insights into our business performance, and delve into our Payroll, Benefits, and HR data to deliver valuable insights and answer critical questions. You will also implement AI-assisted methodologies to accelerate analysis, enhance rigor, and broaden the impact of insights throughout Gusto. We have multiple senior roles open, each focusing on a different segment of our business.Here’s what you’ll do day-to-day:Lead: Tackle ambiguous challenges, design analytical frameworks, and introduce scalable structures across multiple product domains.Strategic Partnership: Work alongside product managers, engineering leads, designers, and operations teams to proactively identify opportunities, align on strategies, and steer data-informed decision-making.Analytical Rigor: Employ advanced statistical methods, causal inference, experimentation, and AI-assisted analytics to identify product performance drivers, distinguishing signal from noise.Experimentation & Analysis: Conduct rigorous experimentation to validate hypotheses and inform product iterations.