This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Reddit is looking for a Measurement Lead to help our advertisers succeed on our platform. This role will be an integral part of the Marketing Sciences team, and overall Revenue organization – driving our value proposition to our clients and their partners by continuously testing, learning and improving the power and performance of Reddit as a media platform. - Daily responsibilities will span advertising measurement execution, measurement strategy, client consultation, vendor relationships, and working closely with Reddit’s sales, product, and product marketing teams. - Leverage measurement results to drive business growth for our clients - developing benchmarks, media & creative best practices, and refinement/optimization to audience and targeting strategy to improve efficiency and effectiveness. - Develop and execute mutual learning plans with clients in order to co-develop Reddit best practices. - Work and consult across a breadth of measurement types including brand lift, conversion/sales lift, multi-touch attribution and media mix modeling. - Work with measurement vendors and with advertisers’ internal analytics teams to understand methodologies and consult with clients on their impact on Reddit. - Support our go-to-market teams with your measurement expertise, industry knowledge, and insights. Qualifications - 8+ years of experience in advertising or analytics at a research vendor, measurement company, social media platform, media owner, client or agency partner – with at least 1 of those years working in digital advertising. - Familiarity with attitudinal survey research, offline and online sales/ROI measurement, impression/attribution/conversion tracking, multi-touch attribution (MTA) and media mix modelling (MMM). - Knowledge of North America Measurement solutions, vendors, and norms. - A knowledge of experimentation and familiarity with the underlying statistical methods. - A strong background in the execution, analysis, and presentation of quantitative advertising research. - Experience working closely with and developing relationships with analytics professionals at advertisers and advertising agencies. - Experience working with measurement vendors, product management, and product marketing teams to bring new services and capabilities to life at a technology company. - A working knowledge of advertising technology, including ad serving, targeting, optimization and relevant data flows. - Exceptional written and oral communication skills – you’re articulate and engaging. 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.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking an experienced Analytics Engineer to join our team, specializing in building scalable and efficient data solutions. The ideal candidate will have expert-level proficiency in SQL, strong knowledge of dbt, and hands-on experience with data modeling and modern ELT (Extract, Load, Transform) processes. - Design and maintain robust data pipelines that efficiently ingest, transform, and deliver high-quality data to support analytics and business intelligence initiatives. - Create dashboards and reports that help the business make informed decisions, ensuring data accuracy and clarity. - Work with business and IT teams to gather needs, solve problems, and support new tools or system changes. - Guide teammates on reporting and data work, sharing best practices for effective data usage. - Pull and analyze data to support the Long Term Care product and drive business decisions. - Support business and I/S partners by working with data repositories on platforms like Teradata, Snowflake, AWS, DB2, Oracle, and SQL Server. Qualifications - Expert-level proficiency in SQL and strong knowledge of dbt. - Hands-on experience with data modeling and modern ELT processes. - 6-10 years of Senior Level Experience. - Solid understanding of data validation, quality controls, and relational databases. - Background in business analysis or business intelligence. - Excellent communication and presentation skills. - Comfortable working in complex technical environments. - Promote a culture of diversity and inclusion. - Able to work remotely with access to a high-speed internet connection. Requirements - Strong analytical, problem-solving, and data interpretation skills. - Experience using SQL, Python, Excel, and Tableau to build reports and drive business insights. - Experience with Report Automation and Process Automation. - Familiarity with data security, risk management, and strategic data management. - Leverage AI-driven tools such as Microsoft Copilot and Snowflake Cortex to automate reporting processes. Benefits - Estimated Salary: Minimum: $90,000 - $115,000, plus annual bonus opportunity. - 401(k) plan with a 2% company contribution and 6% company match. - Work-life balance with vacation, personal time, and paid holidays.

• Lead Sales-Focused Analytics Within Salesforce • Design, develop, and deploy advanced Tableau dashboards and embedded analytics experiences that directly support sales activities, pipeline management, and opportunity execution. • Shape the vision for Salesforce reporting by transforming business questions into analytical frameworks that help sales teams focus on the right actions at the right time. • Translate existing CRM Analytics (CRMA) content into Tableau+ while enhancing clarity, usability, and business impact. • Drive Forward-Looking, Predictive Insights • Apply predictive analytics, statistical modeling, and trend analysis to help the organization anticipate pipeline health, forecast performance, and identify leading indicators of deal success. • Provide strategic recommendations based on data patterns, customer behavior, conversion signals, and territory dynamics. • Be a Thought Partner for Sales Leadership • Collaborate with Sales, Sales Enablement, Strategy, and other stakeholders to understand performance drivers and deliver insights that guide decision-making. • Communicate analytical findings clearly to both technical and non-technical audiences, enabling confident action across the sales organization. • Engineer High-Quality, Scalable Solutions • Integrate and transform data from Salesforce, Azure Synapse, Databricks, and other enterprise systems to power robust analytical models and dashboards. • Work closely with Power BI developers and DSC teammates to ensure platform alignment, governance consistency, and scalable architecture. • Champion data quality, security, and best practices across all Salesforce-embedded analytics. • Contribute to Team Growth and Innovation • Mentor junior analytics developers and foster a culture of learning, curiosity, and continuous improvement. • Identify opportunities to streamline processes, automate insights, and reduce analytical friction for sales users.

• Own delivery and execution • Lead delivery across data initiatives, ensuring roadmaps are executed on time, at high quality, and aligned to business goals • Lead and grow the data organization • Manage and mentor data analysts and data engineers • Set technical direction and raise the bar for analytics, data modeling, and insights • Turn data into decisions • Drive advanced analysis using Python and SQL to uncover trends and influence product, customer experience, and strategy • Build and scale data infrastructure • Own data pipelines and analytics architecture using dbt and Amazon Redshift • Ensure performance, reliability, and scalability as the company grows • Ensure data trust and quality • Define and enforce data quality, validation, and governance standards • Build confidence in analytics and reporting across the organization • Partner cross-functionally • Work closely with Product, Marketing, Customer Support, and Engineering to align data efforts with real business needs • Set culture and best practices • Promote modern data engineering practices • Foster a culture of learning, continuous improvement, and innovation