Responsibilities:

• Develop action-oriented insights to drive the product strategy through observational causal analysis and experiment meta-analysis, and clearly communicate results to stakeholders up to the C-suite to take action based on the recommendations
• Uplevel experimentation practices on the team through guiding design, execution, and deep dive analyses to maximize learnings from A/B tests
• Create new ETLs, tables, dashboards, and other self-serve tools to enable other data scientists and cross-functional partners to find and interact with data seamlessly
• Design, evaluate, and/or measure team-level KPIs to enable quarterly goal setting and demonstrate team impact
• Regularly engage with stakeholders to gather feedback and share progress on work at all stages to ensure alignment between DS and other teams on business goals and outcomes
• Mentor more junior data scientists and business partners in data science best practices and methods to increase data literacy and improve decision making

Required Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Expertise in querying relational databases (SQL) and programming languages (e.g., R / Python)
• Deep understanding of online experimentation (A/B testing), causal inference, and statistical techniques
• Comfortable in innovative and fast-paced environments, and a bias toward action
• Strong technical communication / data storytelling skills and demonstrated ability to discuss complex topics with technical and non-technical audiences alike
• Able to tackle ambiguous and undefined problems by creating an action plan, getting feedback, and iterating

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is $190,800-$267,100 USD

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We're building the largest hyperlocal marketplace the world has seen. Our marketplace is already flourishing in all 50 states and we're just getting started!

As a Senior Data Analyst, you are an independent driver and architect, entrusted with solving Neighbor's most ambitious, complex, and ambiguous problems. You will leverage advanced data analytics to not only execute the data strategy, but also anticipate the challenges that lie ahead. You will bridge the gap between executive vision and technical implementation, pioneering robust data models and pipelines while steering executive-level data strategy and fundamentally shaping the company's data-driven business decisions with your insights.

Primary Responsibilities

• Help build a world-class Data & Analytics team focused on data integrity, business intelligence, data-driven decisions, testing, accountability and research
• Lead the design and implementation of our data modeling layers (Data Lakes/Warehouses), ensuring a 'single source of truth' for a complex, two-sided marketplace
• Beyond SQL, you will build and maintain robust ETL/ELT pipelines and deploy predictive models to forecast and automate insights
• Mentor junior team members and empower non-technical stakeholders to make autonomous, data-informed decisions through world-class BI tooling
• Move beyond 'what happened' to 'what will happen.' Develop statistical frameworks to test hypotheses and measure the impact of new product features
• Act as the primary data partner for Product, Marketing, Sales, Engineering, Finance, and Customer Success leadership
• Become an expert on all aspects of Neighbor's product, user, marketing and other data

Qualifications

• Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) OR 7 years working experience in data analytics
• 5+ years of prior experience as a Data Analyst
• 3+ years of experience solving complex, ambiguous problems independently and presenting results to stakeholders
• Experience with ETL such as data manipulation, organization and cleaning
• Experience modeling data lakes or data warehouses
• Experience with predictive modeling
• Advanced proficiency in reporting and visualization software
• Experience using mathematical, scientific and statistical techniques to analyze data
• Proven track record of using quantitative analysis to solve problems, and drive key business decisions

Additional Information

About Neighbor: Neighbor is the largest and most comprehensive marketplace for self storage and parking, with listings in almost every U.S. city. From storage facilities to neighborhood garages, driveways, and RV spots, Neighbor brings every option together in one simple search.

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This engineering resource will be the cornerstone of our data infrastructure, responsible for extraction, transform, and load of the data that powers our nation-wide, best-in-class marketplace. By implementing software engineering best practices and scalable solutions, this role is critical in empowering the CEO, executive team, managers, and individual contributors with the robust and trustworthy intelligence needed to scale and innovate across our marketplace.

Primary Responsibilities

• Design, implement, and maintain scalable data transformation layers and code-first orchestration frameworks to ensure the delivery of high-fidelity, reusable data models
• Design and build robust pipelines to ingest data from diverse sources (APIs, logs, relational DBs)
• Ensure the reliable and timely execution of all critical data pipelines (ETLs/ELTs) to maintain data integrity and freshness
• Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols
• Develop and refine a robust semantic layer to facilitate self-service analytics, enabling stakeholders to derive insights without exposure to underlying architectural complexities
• Monitor and optimize cloud compute utilization and data model performance to ensure high availability and low-latency reporting during periods of rapid data scaling
• Serve as a strategic technical partner to leadership across Product, Engineering, Marketing, and Finance to align data infrastructure with organizational objectives
• Become a subject matter expert on the product ecosystem, user behavior, and marketing life cycles to better translate raw data into business value
• Serve as a versatile technical resource capable of stepping into the Data Analyst capacity when necessary,performing deep-dive quantitative analysis and building sophisticated visualizations to support executive decision-making
• Mentor the data analytics team on advanced technical methodologies to foster a culture of engineering excellence and data autonomy

Qualifications

• 3+ years of experience in data engineering or analytics engineering
• Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) OR 5+ years work experience as a Data Engineer
• Expert-level mastery of SQL, with the ability to write, tune, and optimize complex queries for high-volume environments
• Strong command of at least one major programming language used for data processing
• Hands-on experience designing and maintaining data lakes or cloud-based data warehouses
• Deep understanding of data integration patterns, including data ingestion, transformation, and automated cleansing (ETL/ELT)
• Experience applying scientific, mathematical, or statistical techniques to analyze data and build predictive models
• Advanced ability to translate complex datasets into actionable narratives using modern business intelligence and reporting tools
• A proven track record of using quantitative analysis to solve ambiguous problems and drive strategic decision-making in a fast-paced environment
• Exceptional ability to collaborate with non-technical stakeholders, translating business requirements into technical specs and vice versa

Benefits

• Generous Stock options
• Medical, dental, and vision insurance
• Generous PTO
• 11 paid company holidays
• Hybrid work model - WFH every Monday
• 401(k) plan
• Infant care leave
• On-site gym/showers open 24/7

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Responsibilities:

• Assume primary responsibility for the capital and liquidity risk management program
• Become a spokesperson for Stripe's credit profile, leading interactions with regulators, financial partners, and other external stakeholders interested in Stripe's financial strength
• Partner with product, finance & strategy, and global partnerships teams to evaluate capital and liquidity implications of new businesses
• Collaborate with tax, accounting, and regulatory legal teams to optimize capital and liquidity efficiency of Stripe's global operating entities
• Work with data science and engineering teams to develop tooling, data management, observability, and analytics to support these efforts

Requirements:

• 10+ years of experience in capital and liquidity management in a regulated banking context, with direct ownership of key components of Basel III-driven capital planning
• Deep knowledge of U.S. banking regulations and their application
• A proven ability to integrate fundamental analysis with applied risk management foundations, either in an accounting or finance discipline
• Demonstrated familiarity with applied statistical techniques and financial modelling principles
• Experience collaborating with data science/engineering teams and facility with large data sets
• Strong written and verbal communications, and comfort leading high-profile presentations
• Track record of strong self-management and ability to handle both high-velocity, short-term deliverables while also progressing longer-term strategic objectives
• Demonstrated curiosity, resilience, problem-solving skills, and desire to contribute to a high-functioning team operating in a dynamic and fast-paced environment

Preferred qualifications include an enthusiastic 'roll up your sleeves' and get things done mindset, the ability to deal effectively with ambiguity and thrive in an unstructured, fast-moving environment, an inclination to solve problems systematically via infrastructure, automation, and repeatable frameworks, a builder's mindset with a willingness to question assumptions and conventional wisdom, and experience with SQL/Python or a willingness to learn.

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