Top Scientist Jobs in San Francisco, CA

Build and scale first-line risk control performance monitoring for financial products. Develop metrics, key risk indicators, statistical baselines, thresholds, automated workflows, and reusable analytical modules. Partner with risk, compliance, product, and engineering teams to improve governance, identify monitoring gaps, evaluate control effectiveness, and support decisions. Lead ambiguous initiatives from definition through adoption while communicating findings, limitations, and recommendations to technical and executive stakeholders.

Supports translational PKPD programs for biologic drug candidates by designing and analyzing in vitro and in vivo ADME and PKPD studies, interpreting animal data to predict human behavior, preparing regulatory documentation, presenting findings, publishing research, managing laboratory programs, and collaborating across research, clinical, safety, bioanalytical, engineering, and regulatory teams.

Lead ML initiatives to improve Sales productivity and automation: define roadmap, design and deploy production ML models and AI agents, build measurement pipelines with analytics engineers, iterate from performance and seller feedback, and act as senior technical partner across product, engineering, and Sales to drive measurable revenue impact.

Supports the development, testing, and evaluation of AI/ML models for educational products. Responsibilities include data collection and cleaning, feature engineering, model validation, analyzing outputs, identifying optimization opportunities, documenting findings, preparing technical reports, and collaborating with Data Science, Engineering, and Product teams. The intern also explores applications in personalized learning, content recommendations, adaptive learning, NLP, generative AI, and responsible AI.

Leads audits and verification of forestry and land-use carbon offset projects under voluntary and compliance standards. Responsibilities include reviewing documentation, quantitative modeling, GIS and remote sensing analysis, field reconnaissance, stakeholder interviews, audit reporting, client coordination, quality management, and training auditors. The role manages complex audit portfolios, oversees contractors, supports ISO and scheme compliance, and requires domestic and international travel.

Design, develop, and evaluate large-scale multimodal foundation models for biological research. Build hybrid LLM and graph neural network architectures, relational foundation models, and distributed multi-GPU training systems. Apply deep learning theory to biological data, transition research prototypes into scalable production systems, publish peer-reviewed research, and mentor junior staff while collaborating across scientific and engineering teams.

Leads drug metabolism and pharmacokinetics strategy across drug development programs, ensuring robust nonclinical packages for regulatory filings, labeling, approvals, and post-marketing activities. Reviews and authors regulatory documents, advises on clinical pharmacology and risk assessments, supports due diligence and licensing integration, and collaborates across scientific and regulatory functions. Provides strategic portfolio leadership, influences development decisions, maintains compliance with global requirements, and mentors future leaders.

Own a focused machine learning project involving packing prediction, packing recommendations, or product understanding. Survey research, prototype and benchmark models, develop production implementations, collaborate with applied scientists and ML engineers on live testing, and present findings. Projects may use multimodal deep learning with images and text, catalog data, and historical fulfillment outcomes.

Lead scientific strategy for Uber Eats logistics and marketplace optimization. Translate complex problems into experiments and production solutions using causal inference and optimization. Drive end-to-end product development, establish experimentation standards, improve model and process efficiency, influence executive roadmaps, and ensure scalable, observable technical solutions. Partner cross-functionally across Uber to improve marketplace resilience and efficiency for eaters, merchants, and couriers.

The Applied Scientist will develop and deploy machine learning products for content understanding, creator sponsorship, advertising, and brand safety. Responsibilities include selecting and evaluating ML approaches, working with behavioral, metadata, text, and video data, prototyping models, deploying them through data pipelines and ML services, and collaborating with scientists, engineers, product teams, and business stakeholders. The role also contributes to innovation in LLMs, computer vision, inference, and model evaluation.

Develop and implement data science strategies for machine learning applications including lead scoring, churn modeling, pricing, personalization, and fraud detection. Own end-to-end initiatives spanning data analysis, feature engineering, model training, inference, and monitoring. Collaborate with engineering, infrastructure, analytics, and business teams to deliver measurable impact, improve data capabilities, and communicate findings to technical and non-technical stakeholders.

The Data Scientist II will lead and execute health economic outcomes research projects, collaborate with stakeholders, and build analytical infrastructure while adhering to regulations.

Leads computational drug discovery research using genomic, clinical, imaging, and other multimodal data to identify cancer targets, patient subtypes, biomarkers, and therapeutic opportunities. Applies machine learning, real-world evidence, and organoid perturbation data while collaborating with AI/ML, biology, clinical, and product teams. Communicates findings to internal leaders and external pharma and biotech partners through presentations and publications.

Characterize monoclonal, bispecific, and antibody-like therapeutics through hands-on laboratory testing using BLI, SPR, ELISA, and developability assays. Analyze and report binding, affinity, kinetics, off-target, and biophysical data; maintain experimental records; support assay automation and cross-functional workflows; and uphold laboratory safety and organization standards.

Leads bioanalytical strategy and method development for small molecules, biologics, and ADCs across discovery, preclinical, and early clinical programs. Develops LC-MS/MS methods, evaluates drug-to-antibody ratio stability, transfers methods to CROs, oversees external studies, interprets DMPK/BA data, authors regulatory reports, mentors scientists, and supports cross-functional planning and resource management.

Leads analytical development activities supporting small-molecule API and drug product development, manufacturing, formulation, stability testing, and regulatory submissions. Selects analytical techniques, oversees contract laboratories and CDMOs, reviews data, manages analytical programs, and prepares technical documentation. Collaborates with medicinal chemistry, DMPK, toxicology, quality, pharmaceutical development, process R&D, project management, and regulatory teams. Serves as a technical subject matter expert and contributes to analytical strategy across multiple projects.

Develop scalable, robust, and sustainable E. coli microbial processes for biologics production. Support process characterization, validation, CMC deliverables, regulatory filings, and Health Authority responses. Collaborate across research, manufacturing, quality, and regulatory functions while representing technical development on cross-functional teams. Champion new technologies, stay current with industry advancements, and contribute to process optimization, including AI-based tools and microbial media development.

Supports clinical trial technology and scientific activities involving eCOA, eConsent, EDC, sensors, and wearables. Reviews protocols, defines requirements, advises on digital health solution design, supports pre-sales and bid defenses, and consults with clients and internal teams. Develops scientific, training, and marketing content; contributes to research, thought leadership, regulatory knowledge, industry forums, and product initiatives while managing multiple projects.

Provides scientific and technical guidance on eCOA, eConsent, sensors, wearables, and other digital health technologies used in clinical trials. Responsibilities include protocol analysis, solution design, client and pre-sales consultation, regulatory alignment, scientific content development, thought leadership, industry engagement, training, and product development input. The role requires expertise in clinical research, drug development, clinical outcome assessments, and dementia scales while coordinating multiple projects across matrixed teams.

Designs and optimizes AI and machine learning solutions, transforms data into insights, and develops production AI systems. Responsibilities include building data infrastructure, speech recognition and NLP tools, and reusable evaluation and monitoring capabilities. The role independently tests AI systems for performance, robustness, bias, explainability, and failure modes; evaluates technical controls; documents findings; communicates recommendations to clients; and mentors junior team members.

Leads the design, development, testing, and evaluation of AI and machine learning solutions. Directs data analysis, modeling, infrastructure, monitoring, and integration efforts while establishing standards for AI robustness, bias, explainability, failure modes, and technical controls. Manages large projects, advises clients, coaches teams, and develops reusable evaluation tools and evidence workflows for responsible AI deployment.

Design and deploy AI systems and machine learning models, perform data wrangling and analysis, and integrate solutions into data infrastructure. Develop scalable AI applications, relational data systems, evaluation tools, automated tests, and monitoring capabilities. Assess AI behavior, robustness, bias, explainability, drift, hallucinations, and guardrails while evaluating technical controls and communicating findings to clients and stakeholders.

Develop and implement AI and machine learning solutions, including algorithms, data models, infrastructure, evaluation tools, automated tests, monitoring, and responsible AI controls. Lead testing for robustness, bias, drift, explainability, hallucinations, and failure modes. Manage client accounts and technical workstreams, review evidence and controls, communicate trade-offs, mentor teams, and maintain delivery and professional standards.

Develop quantitative in vitro protein-protein interaction and displacement binding assays for GPCR drug discovery. Perform hands-on assay development using cellular, biochemical, and membrane-protein systems; apply advanced binding and fluorescence or luminescence methodologies; analyze data and curves in GraphPad Prism; document results; and collaborate with Discovery Biology and multidisciplinary drug discovery teams to advance Septerna’s Native Complex platform.

Leads applied research for oral care, digestive health, and allergy R&D. Develops molecular biology and immunology methods, designs preclinical studies using 2D and 3D cell models, analyzes data, and generates mechanistic insights and scientific claims. Collaborates cross-functionally, communicates findings internally and externally, supports publications and intellectual property, and advances scientific capabilities and thought leadership.