Data Science Director in San Francisco

Sigma is transforming how businesses run by delivering a high performance platform on the modern data architecture. As we grow the engineering team, we are looking for engineering leaders who want to build great products, devising product development, prioritization and execution strategy as well as developing a strong team providing career development, coaching, mentoring, performance evaluations, developing promotion cases, and other managerial responsibilities. About the role: We are looking for a self motivated, engineering leader eager to lead engineering teams with high performing engineers. You will need to be comfortable working in a fast-paced environment and support your teams to deliver incrementally against our roadmap. What you will be doing: Collaborate with cross-functional groups, executive team, field teams to devise business impact product strategy Enable the team to realize their potential and set them for achieving their career development goals Own execution and delivery of roadmaps, to help setup the business and your team for success Partner with the staffing team to recruit and build performing team Instill a strong sense of ownership and accountability within the team wherein members hold each other to a high bar Participate in discussions pertaining to the architecture and implementation techniques to represent, translate and optimize user directives into optimized queries You: Love working with world-class engineers, product managers, and architects to solve complex problems and enable business impact Have 5+ years of technical experience and 2+ years of people management experience Are opinionated and have great product sense make data driven decisions when unblocking the business Have hired, and developed high performing engineering teams Are curious, love to learn and to dig into new technologies to apply them when solving technical challenges Have demonstrated strong technical architecture and engineering skil

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy. The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product. The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge. What you'll do Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model. Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI. Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working. Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge. Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.

Sigma is transforming how businesses allow customers to build apps, agents and dashboards on top of governed enterprise data. Hence, we are growing the design team and looking for designers who are excited to solve challenging problems, deliver impactful capabilities throughout our stack to build world-class technology. You will be part of a talented team of designers with a shared mission to make data easily accessible for all users. We're looking for a Senior Product Designer / Design Engineer who sits at the intersection of interaction design and AI engineering: someone who uses AI to ship faster, builds the skills and evals that make AI more effective, and invents new interaction paradigms for how people work alongside intelligent systems. This isn't a traditional design role. Yes you'll be using Figma, but also writing code with AI, training it, evaluating it, and questioning every assumption about what a "UI" can be when the interface itself reasons. Please note this is a 4 day on-site role in our San Francisco office. What You'll Do Start with AI, stay with AI. Use LLMs to clarify scope, draft specs, surface edge cases, and align your team before committing to a direction, use AI coding tools to build and iterate on the solution itself, and merge code to prod when fits. Prototype in code. Build working interfaces with Cursor and Claude Code, guiding structure, behavior, interaction, motion and UX quality while AI handles implementation. Partner directly with engineering to decide what moves into the product and what stays as a validated spike. Bring it to production. Fix small interaction and refinement issues directly on prod code. Design new AI interaction paradigms for conversational interfaces. Invent and validate novel patterns for how users converse with, direct, and trust AI systems - especially in data contexts where precision and confidence matter. Write evals, skills, and help on tools. Build the scaffolding that makes AI reliabl

At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and engagement for Scale’s offerings amongst our core audiences. We take a data-driven approach to understand our customers’ needs and challenges, ensuring that their voices are reflected in product development and messaging. We partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. We aim to provide valuable insights and resources that help our customers execute on their AI transformation journey. This role will focus on developing and optimizing vertical-specific messaging and content for Scale’s applications business to ensure our messaging resonates with core buyers across verticals. The ideal candidate combines strategic thinking with hands-on execution. You will: Develop clear, compelling messaging for enterprise offerings tailored to key personas within target verticals Create marketing assets, including slide decks, videos, blog posts, and one-pagers, that effectively communicate our value propositions to vertical leaders and support our sales team’s pursuits Lead positioning and sales enablement efforts to drive awareness and engagement for Scale’s offerings. Drive cross-functional marketing programs around target verticals, in conjunction with product, engineering, sales, and growth marketing to create a cohesive customer experience and contribute to pipeline targets Collaborate with field marketing and events teams to develop vertical-specific event strategies, content, and experiences that drive engagement within customer and target accounts Drive customer marketing efforts, creating both strategy and tactics to maximize the value Scale and customers get from our shared success, including case studies, testimonials, visual assets and event particip

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

Scale's mission is to develop reliable AI systems for the world's most important decisions. We provide the high-quality data that powers the world's AI models, and we help enterprises and governments build, deploy, and oversee AI applications that create real impact. As Communications Manager, Corporate and Product, you will help shape how Scale shows up when it comes to our work building enterprise AI, spanning company narrative, product launches, partner communications, media presence, and executive visibility. This role is centered on translating complex enterprise AI deployments and partnerships into clear, compelling narratives that resonate with business and vertical industry audiences. A core focus of the role is pitching and positioning Scale's enterprise wins, product launches, and customer partnerships, including how organizations across industries are using Scale's Generative AI Platform to build, deploy, and oversee AI applications that create real impact. You will also work closely with communications counterparts at partner companies to align messaging and coordinate joint announcements. You will help tell the story of how Scale's enterprise business powers mission-critical AI programs for the world's most consequential organizations, from Fortune 500 companies to leaders across every major industry. In this role, you will partner closely with enterprise product leaders and go-to-market teams, as well as teams across communications, social, and marketing. You will play a key role in strengthening Scale's reputation with enterprise customers, industry analysts, and the broader technology ecosystem. This position reports directly to the Head of Corporate & Product Communications. You Will Support corporate and product communications initiatives with a strong emphasis on Scale's enterprise business, including customer and partnership announcements, product launches, executive visibility, and industry positioning. Help translate co

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

About the Team DoorDash is looking for an analytical and entrepreneurial operator to join our US Marketplace Growth team that is responsible for accelerating new growth bets, most notably with College students and Gen Z. You will dive into data to explain performance at the lowest level of detail, use AI tools to drive reporting efficiency, work with cross-functional partners to report out and explain performance, and help manage a team of College Ambassadors and leads who support our on-the-ground presence at colleges around the country. About the Role The Senior Associate, Marketplace Audience Strategy & Operations role is for truth seekers who enjoy getting scrappy while also examining data, creatively problem-solving on a daily basis, driving insights on business performance trends, using AI to drive efficiency, and working across a cross-functional organization to bring strategies to life. You will directly support new Audience penetration for DoorDash’s largest business unit. On a typical day, you will dive into data to explain performance at the lowest level of detail, broker and manage external ecosystem partnerships, think through how to solve blockers to performance at individual College campuses, work with cross functional teams to build reporting and performance updates for senior leadership, think up new ideas and translate them into an actionable test or new reporting mechanism, and drive the creating of strategic plans that drive execution throughout the business. Our best Strategy & Operations Sr. Associates are motivated, analytical, creative, and have exceptional interpersonal and relationship-building skills. We are currently operating in a hybrid model, some time in-office and some time remote but it is quite flexible! You're excited about this opportunity because you will… Collaborate - Work cross-functionally with teams across DoorDash to understand, report, and drive business performance Strategize - Support the

A bout the Team Our sales and success teams are the heart and soul of DoorDash, helping us partner with top merchants (think restaurants, grocers, convenience stores, retailers) across the country to grow their revenue and help them operate even better. As DoorDash grows both in scale and scope of offering, the strength of our sales engine and organizational structure must grow with it. We are looking for a Manager level in Sales Strategy and Operations to 1. Develop strategic plans in retaining and growing partnerships at scale, 2. Leverage data tools (e.g. SQL) to help enhance sales productivity in targeting and closing the most valuable partnerships. You'll work among our sales, partner management, operations, product, and analytics teams to build the merchant foundation About the Role Within this job posting, we’re hiring for roles on the following team(s): Long-Tail: We are looking for a Sales Strategy Manager to build and execute the Long-Tail Emerging Bets strategy for our Global Sales Vendor organization. You will work closely with internal stakeholders (Sales, Sales S&O, Finance, and more!) to retain and grow Merchants at scale. You will report into the Manager of Revenue Strategy and Operations in our Merchant organization. You’re excited about this role because you’ll… Contribute to post-sales strategy for our top company priorities. This team sits at the nexus of both scaled initiatives and innovative bets at DoorDash focused on catapulting our restaurant partners’ growth. This role will help to develop a strategic vision for SMB Emerging Bets sales strategy, aligning it with DoorDash's overarching business goals. Drive operational excellence in reporting cadences, rigorous pipeline tracking, and sales productivity – leading end-to-end ideation to execution through data-driven insights. Partner with our cross-functional teams to expand and elevate our offering. To retain, optimize, and grow SMBs, this role

The Sales Compensation Manager is vital for scaling and operationalizing Sigma's sales compensation process. You will ensure accurate, timely compensation payouts using expert analysis and refine processes, tools, and reporting to align compensation with business results. This role is ideal for a self-starter who thrives on ownership, data integrity, and cross-functional collaboration between Finance, Revenue Operations, and GTM leadership. Key Responsibilities Commission & Incentive Processing Execute end-to-end commission calculation validation and processing for sales commissions and incentive payouts with high accuracy and precision. Identify, troubleshoot, and resolve calculation discrepancies and stakeholder escalations efficiently. Support compensation accruals and roll-up reporting in coordination with Finance close cycles. Systems & Platform Administration Manage Sigma’s compensation platform with the broader team. Ensure clean data flows between CRM (Salesforce), HRIS, ERP, and comp systems. Plan Governance & Communication Support administration of quota rules, crediting structures, and payout policies. Prepare clear plan documentation, and communication for GTM teams. Cross-Functional Collaboration Partner closely with Finance, Sales Operations, HR/People, and Data to align comp mechanics with business strategy. Identify, prioritize, and implement process improvements that increase accuracy and reduce manual effort. Qualifications: 5+ years of experience in sales compensation, ideally within fast-scaling SaaS orgs. Advanced proficiency with Salesforce CRM, Sigma and spreadsheet tools. Familiarity with consumption-based models and usage-driven GTM strategies. Exceptional attention to detail, robust problem-solving skills, and a strong systems mindset. Effective communication skills with the ability to clearly translate complex compensation logic for both technical and non-technical audiences. Bo

JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Research Analyst – JLL What this job involves: The Research Analyst will join JLL's San Francisco Research team to deliver market intelligence that sets JLL apart. You will analyze San Francisco's industrial, office, and flex markets alongside the economic drivers that shape them. This role combines direct client engagement with hands-on data analysis, positioning you at the intersection of urban economics and commercial real estate. You will grow from foundational market research into automated workflows, quantitative modeling, and independent analysis—building both analytical rigor and technical capability. If you're curious about what drives markets and ready to become data fluent while mastering local real estate dynamics, this role offers a clear path forward. What your day-to-day will look like: Develop expertise on San Francisco's economy, industry composition, demographics, and commercial real estate market to identify trends and emerging opportunities Maintain comprehensive market coverage by tracking significant leasing activity, tenant movements, development projects, sales transactions, and ownership changes Meet regularly with clients and internal teams to present market insights, conditions, and forecasts Produce quarterly reports on San Francisco market

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Senior Manager, Marketing Operations and Strategy is responsible for ensuring marketing efforts are efficient, data-driven, and aligned with business goals through process optimization, technology management, and strategic planning. Key duties include managing budget and org health, leading org-wide annual planning process, managing quarterly reporting (QBRs), overseeing campaign execution and budget, and providing overall operations support to the marketing leadership team. Responsibilities: Strategic planning: Developing and implementing marketing strategies and plans to achieve business objectives, improve brand awareness, and build customer loyalty. Technology management: Evaluating, implementing, and managing the marketing technology stack (e.g., CRM, marketing automation platforms, CMS) and ensuring the team can effectively use these tools. Process optimization: Designing, streamlining, and refining marketing processes to improve productivity, efficiency, and cross-team collaboration. Budget management: Developing, managing, and monitoring the marketing budget, including tracking budget vs forecast, and providing financial reports to management in partnership with Finance. Data analysis and reporting: Working with Analytics to analyze marketing campaign performance data, generating reports for stakeholders, and providing data-driven insights and recommendations for improvement. Collaboration: Acting as a liaison between marketing and other departments to ensure alignment on goals and efforts. Building rapport with the Chief of Staff community and working with on cross-company initiatives and planning. Team support: Training and supporting marketing staff, and providing internal support and training on marketing platforms. Experience: 7+ years of experience in operations or