PrizePicks

Marketing

• Own Integrated Marketing Strategy for Tentpoles: Lead the development of integrated marketing strategies for key sports seasons and tentpole moments (e.g., NFL, NBA, MLB)
• Drive End-to-End Campaign Leadership: Oversee campaign planning and execution across paid, owned, and earned channels
• Lead Go-to-Market Planning: Partner closely with Product Marketing, Product, Promotions and other channel marketing teams
• Set Campaign Direction & Briefing Standards: Establish clear campaign frameworks and messaging direction
• Ensure Cross-Channel Alignment: Act as the central strategic connector across Marketing functions
• Own Performance & Optimization Strategy: Define success metrics to evaluate campaign performance
• Elevate Execution & Team Output: Provide direction, feedback, and prioritization support to junior team members
• Drive Operational Excellence: Identify and implement improvements to campaign planning and workflow management

Senior Integrated Marketing Manager

Payroll

• Manage and process payroll for all employees across multiple states/jurisdictions in a timely and accurate manner.
• Ensure compliance with federal, state, and local wage and hour laws, tax regulations, and reporting requirements.
• Oversee payroll system functionality, upgrades, and integrations with HRIS, accounting, and benefits systems.
• Maintain payroll records and ensure data accuracy, confidentiality, and integrity.
• Manage year-end activities, including W-2s, 1099s, and other required filings.
• Respond to employee payroll inquiries and resolve discrepancies in a professional and timely manner.
• Collaborate with HR and Finance teams on compensation and benefits programs as they relate to payroll.
• Develop and maintain payroll policies, procedures, and controls to improve efficiency and mitigate risks.

Payroll Manager

Product Manager

• Identify opportunities to innovate and improve tools to enable Marketing to execute campaigns, leverage data-driven insights, and improve spend performance
• Set the strategy for how Martech, new member offers, and our referral program operates
• Execute on our team’s product vision, strategy, and roadmap
• Own the end-to-end product lifecycle, from ideation to launch and ongoing optimization.
• Define and execute on technical requirements, launch strategy, and overall vision of the product.
• Work closely with engineers, designers, and a variety of stakeholder groups to define, build, and iterate on a best-in-class user experience.
• Partner with Paid Marketing to drive efficient acquisition spend.
• Deeply understand the Prediction and DFS customer acquisition landscape
• Champion a data-driven approach to product decision-making.
• Partner closely with acquisition experts to grow your skill set
• Our team is growing rapidly. We want you to grow with it.

Senior Product Manager – MarTech

Engineer

• Own the Pipeline: Support and optimize application security tooling (SAST, SCA, Secrets Detection) within our CI/CD pipelines to provide accurate, actionable, and prioritized alerts to devs.
• Be a Security Champion: Act as the primary security partner for Engineering and Product teams, ensuring security is baked in from the design phase through deployment.
• Threat Modeling: Lead collaborative threat modeling exercises to identify architectural risks before code is even written. Partner with penetration testing teams to translate these threats into targeted testing scenarios for high-risk functions.
• Code-Level Remediation: Don’t just tell devs what is wrong—show them how to fix it by performing deep-dive code reviews and providing actionable remediation guidance.
• Secrets Management: Help lead the charge in identifying and removing hard-coded secrets, moving the org toward more secure, automated secret management practices.
• Bug Bounty & Research: Help manage our bug bounty program by triaging submissions, working with researchers, and validating fixes with our engineers.
• Secure AI Integration: Serve as the security consultant for AI/ML initiatives. Partner with engineering to design secure "LLM-backed" features, focusing on prompt injection prevention, data privacy/sanitization, and secure integration of third-party AI APIs.
• Incident Response: Support the team during application-related security incidents, bringing your deep knowledge of code and logic to the table.
• Feature Validation: Perform security assessments on new features to help identify logic flaws that automated scanners might miss. Partner with our penetration testing team on high-risk releases to exchange knowledge and continuously sharpen your offensive security skillset.
• Strategic Communication: Translate technical vulnerabilities into business risk. You’ll be responsible for documenting and presenting findings in a way that is actionable for engineers and understandable for leadership.

Senior AppSec Engineer

Full-stack Engineer

• Own technical direction: Set and evolve the technical standards, architecture, and best practices for your team’s mobile features, ensuring long-term scalability and maintainability of the app.
• Lead the hardest problems: Own the design and delivery of the team’s most complex, highest-scope projects — the ones that require deep technical judgment and cross-system thinking.
• Drive team efficiency: Identify and implement improvements to developer tooling, build pipelines, and development workflows that enable the entire team to iterate faster and ship with more confidence.
• Establish engineering practices: Define and enforce standards for component architecture, testing, accessibility, performance, and mobile deployment across the team.
• Mentor all engineers: Provide mentorship to engineers at every level on the team, shaping technical growth, raising the quality bar, and fostering a culture of continuous improvement.
• Collaborate at the organizational level: Work with Engineering Managers, Product leadership, and other Staff/Principal engineers to align technical strategy with business objectives.
• Own cross-stack integration: Ensure the mobile app integrates effectively with backend services (Go and Rails), driving consistency in API contracts and data flows across the platform.
• Participate in on-call rotation: Own systemic reliability improvements and lead incident response for the most critical production issues.

Staff Software Engineer, React Native

Platform Engineer

• Build Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, setup platform for transitioning experimental Data Science models into robust, high-availability production services.
• Real-Time Inference at Scale: Build automation for deploying low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Feature Engineering & Data Strategy: You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
• End-to-End MLOps: You will work with the Infrastructure team to build and operate core ML platform components for training and experimentation enablement considering developer experience. You will champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability for ML systems to ensure data drift and model degradation are caught and addressed instantly.

Senior Machine Learning Platform Engineer

• Build Scalable Data Platform: Design and build the Data platform for Batch and Streaming use cases. You will build and maintain a platform with cutting-edge technologies and enable data users by building data catalog and data lineage capabilities. You will be contributing to design and enforce robust data security architectures and controls.
• Real-Time data platform at Scale: Build platform for deploying low-latency services to pipe data for streaming or near real time use cases. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Data Platform Ops: You will champion best practices for model deployment, monitoring, and CI/CD for Data pipeline deployment. You will enable complete observability for batch and streaming data platform and ensure the availability of 99.99%

Data Platform Engineer

Data Scientist

• Own end-to-end media modeling (MMM), from data preparation and model development, to validation, calibration, and stakeholder delivery
• Design, launch, and maintain incrementality testing frameworks, in partnership with paid media partners, including geo-holdout and platform-native lift study designs
• Translate model outputs into actionable budget allocation and channel investment recommendations
• Partner with channel leads to develop and maintain a structured learning agenda across paid media
• Automate recurring measurement processes to improve accuracy, scalability, and speed-to-insight
• Contribute to raising the analytical bar across the team through code review, documentation, and knowledge sharing

Senior Data Scientist, Acquisition Marketing

Machine Learning Engineer

• Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services.
• Real-Time Inference at Scale: Steer the design and deployment of low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Feature Engineering & Data Strategy: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
• End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.