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Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

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Principal Software Engineer – Data Platform

San Francisco, CA (Remote Eligible – US Only)

$230K-$280K base + equity

Are you ready to lead the design and build of a world-class data platform from the ground up?

A high-growth, product-led tech company is looking for a Principal Software Engineer to lead the build-out of a modern, scalable data platform from the ground up. If you’re excited about solving massive data challenges and shaping the infrastructure that supports real-time analytics and AI/ML at scale, this role is for you.

As the most senior technical IC on the Data Platform team, you’ll partner with leadership across Engineering, Product, Security, and Compliance to design a low-latency, cloud-native data architecture using best-in-class tools like Kafka, Iceberg, ClickHouse, Tinybird, and Snowflake.

Why this role?

• Join a growing Data Platform team
• Own the technical vision and architecture end-to-end
• Tackle petabyte-scale data challenges and real-time streaming use cases
• Work with a cutting-edge tech stack (Kafka, Iceberg, ClickHouse, Snowflake, etc.)
• Drive platform evolution to support AI/ML and company-wide analytics

What You’ll Do

• Design and build a next-gen data platform to power product and internal use cases
• Architect for batch + streaming, scalability, fault tolerance, and low latency
• Lead data modeling, warehousing, governance, and ingestion best practices
• Champion engineering excellence and mentor senior engineers
• Align technical decisions with long-term business strategy
• Optimize for performance, cost, and resiliency in a modern cloud environment

What We’re Looking For

• 8+ years of experience in data engineering or platform architecture
• 5+ years at the Principal Engineer level or equivalent
• Deep expertise with Kafka (and its ecosystem), streaming data systems
• Strong experience with ClickHouse, Iceberg, Snowflake, or similar tools
• Cloud-native architecture expertise (AWS, GCP, or Azure)
• Track record of designing data systems for compliance and governance
• Experience scaling systems to support petabyte-level workloads
• Excellent communication, collaboration, and leadership skills
• Bonus: Experience enabling AI/ML platforms or preparing for IPO-scale growth

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Senior Data Engineer

San Francisco, CA

$180-240K base + equity

We’re partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.

You’ll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.

What you’ll do

• Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
• Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
• Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
• Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
• Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
• Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
• Champion data quality and governance across classification, ownership, access policies, and data lifecycle management

What we’re looking for

• 5+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
• Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
• Experience with Kafka and streaming data systems, with working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture experience across AWS, GCP, or Azure
• Exposure to designing data systems that meet compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to contribute as a technical voice across engineering and business stakeholders

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Staff GTM Data Scientist

Location: Remote

Salary: $190-220k base

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role sitting at the heart of their product and go-to-market strategy. This isn’t a reporting role or a dashboard-builder position. It’s for someone who can drive a genuine shift toward data-driven decision making across the organization, and who has the technical depth and communication skills to bring leadership along with them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focusing on high-leverage questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to assess the real impact of product and business changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of GTM Data, acting as a strategic thought partner across Product, Marketing, Finance, and Engineering. The company is at an inflection point in how it uses data, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still maturing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

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Senior Analytics Engineer

Location: Remote

Salary: $150-170k base

We’re partnering exclusively with a fast-growing SaaS company to find a Senior Analytics Engineer to join their data team. This is a high-impact, high-autonomy role sitting at the intersection of data engineering and analytics, perfect for someone who takes pride in building data foundations that the whole business relies on.

What You’ll Be Doing

• Designing and building dimensional data models in Snowflake that underpin analytics across the business
• Developing and optimising dbt models to turn raw source data into clean, trusted datasets
• Partnering with analysts and business stakeholders to translate their needs into scalable data solutions
• Implementing data quality checks and owning the reliability of analytics datasets
• Contributing to data governance including PII handling, metadata management, and documentation
• Supporting strategic analytics across customer journeys, revenue metrics, and product usage
• Mentoring junior team members and championing best practices

What We’re Looking For

The company runs a best-in-class modern data stack built around Snowflake, dbt, and Monte Carlo, with data flowing in from Salesforce, HubSpot, Recurly, and core product databases. The team is evolving toward an AI-enabled, domain-oriented data organisation, so there’s real scope to shape the architecture, not just maintain it.

Essential:

• 5+ years in analytics engineering, data engineering, or a similar data-focused role
• Expert-level SQL: complex queries, CTEs, window functions
• Strong hands-on dbt experience
• Snowflake (or equivalent cloud warehouse: BigQuery, Redshift)
• Solid understanding of dimensional modelling and data warehouse design patterns
• Experience with SaaS metrics: MRR, churn, CLV etc.
• Python for data work or automation
• Familiarity with data orchestration tools (Airflow / MWAA)
• Comfortable working remotely and cross-functionally with distributed teams

Nice to have:

• Experience with reverse ETL tools such as Hightouch
• Exposure to BI tools (Hex preferred)
• Understanding of data mesh or domain-oriented architecture concepts

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Staff Growth Product Analyst

US Remote

$200-240k base + equity

About the Role:

We’re looking for a Staff Growth Product Analyst to drive impactful growth analytics for an innovative AI-driven development platform that’s transforming how developers create and deploy user interfaces. Leveraging cutting-edge AI technologies, this platform enables rapid prototyping and significantly accelerates product development, enhancing user growth, engagement, and overall developer experience.

Role Highlights:

• Deep dive into user behaviors, journeys, and growth funnels to uncover opportunities for enhanced engagement and acquisition.
• Generate actionable insights aimed at boosting critical growth metrics like DAU, MAU, and user retention.
• Design, execute, and analyze A/B tests to drive informed decision-making and product improvements.
• Influence strategic decision-making through rigorous data analysis and compelling recommendations.
• Collaborate cross-functionally with product managers, engineers, data scientists, and growth marketers to drive continuous product improvement and iteration.

Who You Are:

• You have 7+ years of proven expertise in growth and product analytics, ideally within early-stage or innovation-driven product environments.
• You’re adept at conducting thorough funnel analyses, spotting rapid experimentation opportunities, and recommending actionable product enhancements.
• You thrive on solving complex analytical problems with high energy and intellectual rigor.
• Experienced with modern data stack (e.g., Snowflake, dbt, Preset, Hashboard, Kafka, Fivetran, Omni, Hex, Sigma, SQL, Python).
• You have previous experience (or a strong interest) in working with AI or machine learning-driven products.

Ideal Fit: You’re a driven, collaborative analytics expert passionate about influencing groundbreaking products. Excited by high-paced, innovative environments, you’re motivated by measurable impact and shaping the future of developer-focused, AI-powered technologies.

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Staff Data Platform Engineer

US Remote

$200-245k base + Equity

We’re working with a rapidly expanding consumer tech startup that recently raised $125M in Series D funding. As they continue to scale, they’re looking to hire a Staff Data Engineer to join their growing data team. If you have a strong foundation in software engineering, a collaborative mindset, and a passion for driving data strategy, this is the opportunity for you!

The Role:
As a Staff Data Engineer, you’ll be a crucial part of the team, ensuring data is accessible, reliable, and actionable across the company. Working alongside engineers, data scientists, and business teams, you’ll help build scalable data platforms that drive key business initiatives and enable data-driven decision-making.

What You’ll Do:

• Collaborate with engineering, data science, and business teams to understand data needs and implement effective solutions aligned with business objectives.
• Design and build scalable data infrastructure and pipelines to handle high volumes of data as the company grows.
• Lead the design and optimization of data architecture, ensuring it’s secure, high-performing, and scalable.
• Improve and streamline data pipelines to provide fast, reliable access to high-quality data.
• Contribute to the design of reporting frameworks and analytics tools that empower teams to make data-driven decisions.
• Work with security teams to ensure data privacy and compliance standards are met.
• Mentor junior engineers, share expertise, and promote best practices across the team.
• Stay updated on new technologies and suggest improvements to enhance processes and tool efficiency.

You’re a Great Fit If:

• You have 7+ years of experience in data engineering.
• You’ve worked at a leading consumer tech company known for engineering excellence.
• You’re an expert in SQL, Python, and data platform development.
• Nice-to-have: Familiarity with AWS, Kubernetes, Redshift, Athena, S3, and Airflow.
• You have hands-on experience with complex data infrastructures and optimizing data pipelines.
• You’ve led large-scale data projects that had a significant impact on your organization.
• You thrive in collaborative environments and have strong communication skills.
• You have an ownership mindset and take responsibility for delivering results.

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Senior Analytics Engineer
Location: Los Angeles, CA (Hybrid)

Salary: $150-200k base

We’re partnering with a rapidly scaling, mission-focused advanced technology company operating at the intersection of AI, hardware, and large-scale systems. Their software platform aggregates and operationalizes complex, real-time data to power critical decision-making in high-stakes environments.

As the company continues to grow, they are hiring a Senior Analytics Engineer to help architect and scale the core data foundation of the business.

The Opportunity

You will design and implement the core data models that represent how the organization operates across functions such as Finance, Supply Chain, Manufacturing, People, and Operations. These models will power internal applications, workflows, and metrics used by leadership to run the business.

You’ll sit at the intersection of analytics, engineering, and operations, helping build a scalable “digital twin” of a fast-moving, technically complex organization.

What You’ll Do

• Define and develop domain-level data models that reflect real business operations
• Build secure, scalable, and extensible transformations and data pipelines
• Own ingestion and egress frameworks across multiple source systems
• Contribute to architectural decisions and roadmap direction for the data platform
• Partner cross-functionally with engineering, product, and operations stakeholders
• Translate ambiguous business questions into structured, production-grade data systems
• Drive adoption of self-serve data applications beyond traditional BI

What They’re Looking For

• 5+ years of experience in Analytics Engineering, Data Engineering, or highly technical analytics roles
• Advanced SQL skills and strong experience with Python or similar languages
• Demonstrated success building scalable, reusable data models in fast-paced environments
• Experience with modern data stack tools such as dbt, Redshift, and BI platforms; exposure to enterprise data platforms is a plus
• High degree of ownership and comfort operating autonomously
• Strong communication skills and ability to partner with non-technical stakeholders
• Ability to obtain and maintain a U.S. Secret security clearance

This is a high-impact opportunity to shape foundational data systems inside a company solving complex, real-world problems at scale. If you’re excited by building data applications that influence how an organization operates, click apply to learn more.

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Staff Data Scientist (Product)

Location: Remote

Salary: $190-220k

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role embedded in their product organization. This is for someone who combines deep statistical expertise with the ability to influence how an entire company makes decisions – not just someone who runs experiments, but someone who builds the culture and infrastructure around them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focused on high-leverage product questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to measure the real impact of product changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to meaningful business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of Product Data, acting as a strategic thought partner across Product, Engineering, Finance, Design, and Product Marketing. The company is at an inflection point in how it uses data to make product decisions, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still developing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

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Staff Analytics Engineer

Location: Remote
Salary: $200-250k

Are you a data expert ready to drive transformative analytics at a cutting-edge cloud platform company? This fast-growing Series C innovator is revolutionizing how teams build, preview, and deploy high-performance digital applications.

About the Role

The Staff Analytics Engineer will lead the design and implementation of robust data models and pipelines, enabling business units to uncover insights and make data-driven decisions. This role is a unique chance to collaborate with engineering, product, and business teams, building scalable analytics systems that power operational efficiency and growth.

Key Responsibilities

• Design and maintain scalable data models and pipelines to serve as a single source of truth across the enterprise.
• Develop tools to enhance data accessibility, auditing, and validation, ensuring consistent, trustworthy datasets.
• Partner with cross-functional teams to uncover actionable insights and support decision-making.
• Build self-service analytics tools and dashboards for key stakeholders, streamlining workflows.
• Collaborate on advancing the company’s data platform using cutting-edge tools like dbt, Snowflake, and Superset.
• Lead initiatives to improve data quality, governance, and discoverability, ensuring alignment with business goals.

About You

• 8+ years of experience in analytics engineering or a similar role in a modern tech company.
• Advanced proficiency in SQL, with experience working on complex datasets.
• Expertise in data platforms like Snowflake or BigQuery and transformation tools like dbt.
• Familiarity with programming languages such as Python, Java, or Go.
• Experience with BI tools like Hashboard or Superset, and a strong grasp of schema design and dimensional modeling.
• Strong communication skills and the ability to collaborate in a fast-paced environment.

Be part of a forward-thinking team where data is at the core of every decision. If you’re passionate about transforming data into meaningful insights, this role offers the chance to work on impactful projects, collaborate with top talent, and make a lasting difference.

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Senior Data Platform Engineer

Location: Los Angeles, CA

Salary: $160-200k base

We’re partnering with a fast-scaling, mission-driven advanced technology company building complex software and hardware systems deployed in real-world environments. Their platform processes and operationalizes high-volume data to power critical decision-making across the organization.

They are hiring a Senior Data Platform Engineer to design and scale the core data infrastructure that supports company-wide operations.

The Role

As a Senior Engineer on the Data Platform team, you will:

• Design and build scalable data pipelines and transformation frameworks
• Own ingestion and egress systems that unify multiple operational data sources
• Develop reliable, secure data models that power internal data products and applications
• Partner with engineering, product, and operations to translate business needs into production-grade systems
• Advocate for best practices across testing, CI/CD, data modeling, and security
• Debug and optimize complex transformation pipelines in production environments

What They’re Looking For

• 5+ years of experience in data engineering or backend engineering
• Strong programming skills in Python or similar languages
• Experience with Spark, PySpark, SQL, and dbt
• Familiarity with large-scale data platforms and cloud environments (AWS, Azure, or GCP)
• Experience with containerization and modern deployment practices
• Ability to operate autonomously in fast-moving environments
• Strong ownership mindset and attention to security best practices
• Must be a U.S. Person due to export-controlled information requirements

This is a high-impact role focused on building durable data systems that directly support operational execution at scale.

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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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