Senior Data Scientist, Graph Machine Learning - San Francisco Only

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 MITHRLAt Mithrl, we envision a future where innovative medicines are delivered to patients in mere months, not years, and where scientific discoveries unfold at the speed of thought.Mithrl is pioneering the world’s first commercially available AI Co-Scientist, a groundbreaking discovery engine that converts complex biological data into actionable insights within minutes. Scientists interact using natural language, and Mithrl provides real analysis, innovative targets, hypotheses, and patent-ready reports.Our impressive track record includes:12X year-over-year revenue growthEndorsed by leading biotech firms and major pharmaceutical companies across three continentsFacilitating significant breakthroughs from target discovery to patient outcomes.ABOUT THE ROLEWe are seeking a Data Scientist specializing in Knowledge Graphs to develop and enhance the biological knowledge layer that supports the Mithrl AI Co-Scientist. Your primary focus will be to aggregate and harmonize the most critical biological data sources globally, curating the relationships that enable our system to reason across various pathways, targets, diseases, compounds, and multimodal datasets.You will be responsible for gathering data from public consortia and well-maintained peer-reviewed sources to create a coherent, versioned knowledge graph. This includes identifying new node types, defining relationship schemas, harmonizing variable IDs, and ensuring metadata consistency across all integrated sources. Additionally, you will build automated curation pipelines that enrich and refine the knowledge graph through both data-driven approaches and domain knowledge.Beyond data ingestion and curation, you will develop tools and frameworks that empower users to interact with the knowledge graph and create their custom graphs based on the insights generated within Mithrl. Your contributions will lay the groundwork for pathway reasoning, target scoring, evidence aggregation, and multimodal interpretation within the AI Co-Scientist.WHAT YOU WILL DOAggregate, harmonize, and version high-value public biological datasets such as CellxGene, Gemma, ARCHS4, ENCODE, GTEx, TCGA, etc.Ingest well-maintained peer-reviewed knowledge bases such as OpenTargets, HPA, and similar resources.Create automated pipelines to curate and broaden relationships within the knowledge graph.Define and evolve relationship schemas, ensuring accuracy and consistency throughout.

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 Windfall, a pioneering people data and AI company, where data science is at the heart of our mission. We are dedicated to transforming how organizations understand and leverage people data by equipping leading commercial and nonprofit partners with precise, actionable predictive models.We are seeking a product-focused Senior or Staff Data Scientist to be part of our Modeling & AI team. In this pivotal role, you will directly influence customer success by developing custom propensity models that tackle our clients' most pressing challenges. Collaborating closely with customer data and Windfall's extensive data resources, you will craft innovative solutions and create comprehensive modeling pipelines that convert data into tangible value.This position offers a unique chance to witness your contributions in action, working hand-in-hand with our clients to develop a range of models, from sophisticated marketing and lead scoring to donation likelihood models that enhance the missions of the world's leading nonprofit organizations.

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 SoFi, a leading personal finance company, as a Data Scientist where you will leverage data to drive strategic decisions and enhance user experiences. In this role, you will analyze complex datasets, build predictive models, and collaborate with cross-functional teams to propel our innovative solutions forward.

About SesameAt Sesame, we envision a future where computers possess lifelike qualities, enabling them to see, hear, and interact with us in natural and human-like ways. We are dedicated to creating innovative voice agents that seamlessly integrate into our daily lives. Our talented team comprises founders from Oculus and Ubiquity6, along with seasoned professionals from Meta, Google, and Apple, boasting extensive expertise in both hardware and software development. Join us as we redefine the boundaries of technology and create a world where computers come to life.About the RoleAs a Machine Learning Scientist at Sesame, you will play a pivotal role in advancing our product goals through innovative research. We seek a detail-oriented individual with a strong background in Natural Language Processing (NLP), Speech Recognition, and/or Computer Vision, particularly with a focus on deep learning methodologies. You will stay abreast of the latest research and leverage your creativity and intuition to devise novel solutions tailored to our unique applications.Responsibilities:Contribute to the design and enhancement of machine learning models across diverse modalities.Engage with the complete ML stack, including model architecture, data curation, evaluation metrics, and training and inference infrastructure, while conducting research and experimentation.Identify and adopt promising techniques from existing literature, while innovating new methods as necessary to meet our distinct objectives.Required Qualifications:Demonstrated ability to work independently in environments characterized by high ambiguity.Published research in NLP, Speech Recognition, or Computer Vision focused on large-scale deep learning projects.Proficient understanding of cutting-edge advancements in artificial intelligence.Bachelor’s degree or higher in Computer Science or a related field.Preferred Qualifications:Master’s or PhD degree is preferred.Experience working on product development.Familiarity with startup environments.Sesame is committed to fostering a workplace that values, respects, and empowers everyone. We welcome applicants from diverse backgrounds, embracing all aspects of identity, race, gender, orientation, and ability. We also provide reasonable accommodations for individuals with disabilities — please contact careers@sesame.com for assistance.

Join Metriport as a Data Scientist and be at the forefront of data-driven decision making! In this role, you will leverage advanced analytics and machine learning techniques to derive insights from complex datasets, enhancing our product offerings and driving strategic initiatives.

Position OverviewAt Sentra, we are pioneering the development of organizational superintelligence through innovative memory infrastructure that intelligently processes time, causality, and context. As a Machine Learning Research Scientist, you will address fundamental challenges in knowledge representation, temporal reasoning, and semantic compression. Your mission will be to design and implement sophisticated systems that preserve the execution state for entire organizations, transforming millions of micro-events into robust knowledge and identifying patterns for predicting future events.Key ResponsibilitiesDevelop LLM-powered information extraction pipelines to convert unstructured communications and textual data into structured entity-relationship models.Create memory consolidation algorithms that validate information through multiple observations, merge duplicate entities, and efficiently prune transient data.Architect temporal knowledge graphs that represent organizational execution states as dynamic, continuously updated frameworks instead of static records.Implement graph attention mechanisms and reasoning systems for intricate causal queries regarding blockers, dependencies, and outcome patterns.Conduct research on lossy semantic compression using information-theoretic principles to distill event streams into query-relevant long-term memory.Design entity resolution systems that effectively manage identity evolution, where entities may merge, split, and transform over time.Construct meta-learning systems that uncover organizational patterns and discern when current situations align with historical indicators of success or failure.Innovate privacy-preserving cross-organizational learning approaches utilizing federated learning and differential privacy techniques.Publish research findings and actively contribute to the wider research community focused on knowledge graphs and organizational intelligence.

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 Altos Labs as a Machine Learning Scientist or Senior Machine Learning Scientist and be at the forefront of innovative research in the virtual cell space. Our team is dedicated to advancing the field of machine learning and its applications in biological research.

Sciforium is an innovative AI infrastructure company specializing in the development of state-of-the-art multimodal AI models, alongside a proprietary high-efficiency serving platform. With substantial financial backing and direct collaboration with AMD, including hands-on support from AMD engineers, our rapidly growing team is dedicated to building the comprehensive stack that powers cutting-edge AI models and real-time applications.Role OverviewWe are on the lookout for a highly skilled and visionary Data Scientist to spearhead the strategy and creation of vast datasets essential for our foundational models. In the realm of Large Language Models (LLMs), we recognize that data is the key competitive advantage. This role will encompass the entire data lifecycle—from extensive web-scale crawling to the meticulous creation of human-aligned datasets that dictate model behavior.The ideal candidate will embrace data as both a large-scale engineering challenge and a complex analytical puzzle. Your responsibilities will extend beyond simply delivering data; you will design taxonomies, filtering heuristics, and post-training pipelines to ensure our models excel in reasoning, safety, and multimodal comprehension.Key ResponsibilitiesFoundation Dataset Strategy: Oversee the comprehensive creation of pre-training datasets for LLMs, defining the optimal mix of web data, code, literature, and technical documents to enhance downstream model performance.Petabyte-Scale Curation: Innovate and implement advanced pipelines for data cleaning, deduplication (exact and fuzzy), and high-quality signal extraction from vast amounts of unstructured data.Post-Training & Alignment Data: Direct the creation of high-quality post-training datasets, including Supervised Fine-Tuning (SFT) instructions, multi-turn dialogues, and preference modeling data (RLHF/DPO).Multimodal Expansion: Lead the acquisition and processing of vision and video data, addressing the challenges of multimodal alignment, video compression, and temporal data consistency.High-Performance Engineering: Create high-throughput data processing scripts utilizing Python, employing multiprocessing and multithreading to manage large-scale ingestion and transformation without performance bottlenecks.Data Profiling & Analysis: Perform in-depth statistical analysis on training datasets to uncover biases, knowledge gaps, and quality regressions, ensuring a mathematically balanced model diet.Synthetic Data Generation: (Added Value) Develop pipelines to generate high-quality synthetic datasets that enhance model training and capabilities.

Join our dynamic team at tempo-xyz as a Data Scientist, where you'll harness the power of data to drive impactful insights and strategic decision-making. You'll collaborate with cross-functional teams to analyze complex datasets, develop predictive models, and communicate findings to stakeholders. This is an excellent opportunity for innovative thinkers eager to make a difference through data-driven solutions.

ABOUT MITHRLAt Mithrl, we envision a future where groundbreaking medicines are delivered to patients within months rather than years, and scientific discoveries unfold at an extraordinary pace.We are pioneering the first commercially available AI Co-Scientist, a revolutionary discovery engine that converts chaotic biological data into actionable insights in mere minutes. Scientists can pose questions in natural language, and Mithrl provides comprehensive analyses, identifies novel targets, formulates hypotheses, and generates patent-ready reports.Our remarkable growth:Achieved 12X revenue growth year-over-yearTrusted by leading biotech firms and major pharmaceutical companies across three continentsFacilitating significant breakthroughs from target discovery to improved patient outcomes.ROLE OVERVIEWWe are seeking a Data Engineer specializing in Knowledge Graphs to develop the foundational infrastructure for Mithrl’s biological knowledge layer. You will collaborate closely with the Data Scientist focused on Knowledge Graphs to convert curated knowledge sources into scalable, dependable, and production-ready systems that support our entire platform.Your responsibilities will include constructing ETL pipelines for extensive biological datasets, designing schemas and storage models for graph-structured data, and developing APIs that enable ML engineers and application teams to efficiently query and utilize the knowledge graph. Additionally, you will be responsible for ensuring the reliability, performance, and versioning of the knowledge graph infrastructure across releases.This position serves as a vital link between biological knowledge ingestion and the high-performance engineering systems that apply it. If you are passionate about data modeling, schema design, graph storage, ETL processes, and scalable infrastructures, this role offers a unique opportunity to significantly influence the intelligence layer at Mithrl.KEY RESPONSIBILITIESDevelop and maintain ETL pipelines for large-scale public biological datasets and curated knowledge sourcesDesign, implement, and refine schemas and storage models for graph-structured biological dataCreate effective APIs and query interfaces that enable internal teams and AI systems to access nodes, relationships, pathways, annotations, and perform graph analyticsCollaborate with Data Scientists to operationalize curated relationships, harmonized variable IDs, metadata standards, and ontologies.

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 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 TacitTacit is an innovative, early-stage deep tech startup located in San Francisco, pioneering advanced hardware solutions that revolutionize human-computer interaction. With prestigious backing from General Catalyst, Khosla Ventures, and Greylock Partners, our founding team comprises experts from Stanford, BrainGate, Oculus, and Tesla. While we are still in stealth mode, our team is passionately addressing avant-garde engineering challenges to create groundbreaking products.About the RoleAs a Data Scientist Intern, you will join our Machine Learning and Research team, focusing on the development of state-of-the-art tools and methodologies for data processing and analysis. Your responsibilities will include designing, executing, and analyzing experiments using our unique systems, interpreting results to guide future data collection, hardware design, and enhancing our decoding algorithms. This role will involve hands-on experience with our custom hardware signals and examining performance scaling across diverse user groups.What You'll DoDesign, implement, and test algorithms for extracting features from bio-signals to enhance machine learning models.Rapidly iterate on experiments to evaluate new hardware prototypes and improve data collection methods.Develop visualization tools and establish metrics for data quality assessment.Collaborate with hardware and electrical engineers to optimize the sensing stack.Work alongside the ML team on data augmentation, multimodal training, and synthetic data experiments to enhance generalization.RequirementsCurrently enrolled in or recently graduated from a PhD program in neuroscience, biomedical engineering, computer science, applied mathematics, or a related discipline.Excellent communication and writing skills.Proven ability to collaborate across multidisciplinary teams and adapt quickly to new domains.Proficiency in Python; experience with PyTorch is a plus.Familiarity with dimensionality reduction techniques and time series data analysis.Strong independent work ethic, flexibility, and resourcefulness.Thrives in a fast-paced startup environment and is eager to contribute independently.Preferred QualificationsExperience with machine learning frameworks and data science tools.

Join Scribd Inc., a leading digital library and subscription service, as a Data Scientist II. In this role, you will leverage data analytics to drive insights and support data-driven decision making across the organization. Collaborate with cross-functional teams to implement machine learning models and enhance our user experience.

Join Us as a Founding Data Scientist and Machine Learning EngineerAmplify Your ImpactYou have achieved remarkable milestones in your career—delivering impactful models, influencing key metrics, and showcasing the transformative potential of data science and machine learning. You have positively affected products that touch millions of lives.Now, envision the possibility of enhancing the entire app ecosystem by extending your influence across numerous products and companies, making every app in users’ pockets smarter, more engaging, and indispensable.Your expertise can empower product teams to innovate faster, captivate users, and drive revenue growth, thanks to the intelligence you develop once and deploy universally.We share this ambition; we have successfully achieved it multiple times at leading organizations like Uber, Apple, Meta, Google, and Chime. Our contributions have generated tens of billions of dollars in impacts for essential products relied on by billions, and we are poised to elevate our influence further.If this resonates with the journey you seek, we invite you to continue reading.Our MissionDashboards recount the past; teams require insights for their next move. Palladio AI serves as the intelligence layer between raw data and decisive action, illuminating product opportunities that translate into genuine growth levers and guiding actions so product teams can iterate with confidence and speed rather than wade through noise.Your RoleYou will be part of a team crafting foundational systems in behavioral modeling, causal inference, forecasting, agentic platforms, and beyond. Your contributions will extend these domains: developing ML and AI models to identify and highlight product opportunities, deploying learning loops that enhance with each release. In essence, you will convert fundamental data science principles into a scalable product across various industries.Beyond technical challenges, you will create a platform that aids real people in making informed decisions, transforming data into clarity and clarity into actionable progress.Your ProfilePassion for Craft and Excellence. You dive into complex datasets, prototype swiftly, and refine until insights shine.Impact-Driven Mindset. 6+ years of experience in production ML/DS; you harmonize scientific rigor with a practical approach—“it ships today, iteration follows.”

Join Hilbert, a pioneering data science-first growth engine that empowers B2C teams with predictive insights into user behavior, revenue drivers, and strategies for sustainable growth. Our innovative platform transforms lengthy decision cycles into actionable insights within minutes.From Fortune 10 corporations to cherished brands such as FreshDirect, Blank Street, and Levain Bakery, teams leverage Hilbert for their growth strategies. We're also collaborating with leading AI organizations to push the boundaries of data science.We are in search of a Lead Data Scientist who possesses a systems thinking approach, deeply understands B2C business challenges, and is capable of developing the models and analyses that drive tangible growth outcomes for major consumer companies — all with the passion and urgency akin to that of a founder.This role transcends the traditional boundaries of data science; you will oversee the entire data science function — from defining problems to model development and measuring business impact — all while working with enterprise clients where feedback loops are rapid and outcomes are critical. If you can articulate the significance of a recommender system to a retailer's profit and loss statement, design adaptable machine learning solutions for various customers, and communicate causal impacts clearly to executives, we want to connect with you.THE ROLEYou will collaborate closely with the founding team, as well as the engineering, product, and go-to-market teams to define, develop, and enhance the data science systems central to Hilbert's operations. Expect to be hands-on daily — building models, conducting analyses, and exploring data — while also establishing scientific direction, ensuring rigor, and expanding the team. Our focus is exclusively on B2C; the challenges we tackle — demand forecasting, customer lifecycle management, personalization, and activation — necessitate a deep understanding of these domains and the ability to translate business context into model architecture decisions. You will thrive in an environment characterized by high autonomy and ambiguity, where data can often be incomplete, messy, or limited.What you'll do:Build — hands-on, every dayDesign and construct machine learning models that drive essential product functionalities: recommendation engines, search relevance, customer segmentation, demand forecasting, and activation strategies.Create configurable, multi-tenant model architectures that can adjust to varying customer contexts, data availability, and business needs without the necessity for complete redevelopment.Develop effective models using available data — focusing on extracting insights from limited, noisy, or sparse datasets.