About the Team

DoorDash’s mission is to grow and empower local economies. By building intelligent, last-mile delivery technology for local cities, DoorDash connects people with the local businesses they care about — helping grow businesses and the communities that support those businesses. This mission is enabled by our 3 key audiences (consumers, merchants & Dashers). 

Although the Audience Insights team is a part of the Marketing structure at DoorDash, it partners with and influences the strategy of different functions across the organization. The purpose of our team is to use our knowledge and expertise to bring the insights needed to the forefront and ensure the voice of our 3 key audiences (consumers, merchants & dashers) is at the core of our decisions. This includes completing research, incorporating tools, synthesizing data, and consulting on projects.

About the Role

As an Audience Insights Manager, you will join our Insights function at a pivotal moment for the business. This role will focus on shaping strategy through a deep understanding of the Canadian consumer, ensuring our decisions across marketing, product, and partnerships are grounded in clear, actionable insights.

You will serve as the primary voice of the Canadian audience, representing local needs and perspectives within broader regional and global conversations that shape the business. Beyond executing research, you will act as a strategic partner to cross-functional teams, contributing to how problems are framed, how decisions are made, and how insights are applied to drive impact.  In this position, you will 

• Lead research that informs key business decisions, including audience understanding, positioning, messaging, and go-to-market strategy
• Design and deliver both foundational and tactical research, spanning areas such as brand health, creative effectiveness, and audience needs
• Identify drivers of behavior, perception, and growth opportunities, translating them into clear implications for the business
• Influence decisions across marketing, product, and partnerships, acting as a trusted thought partner to cross-functional stakeholders
• Establish and evolve insight frameworks, tools, and processes that improve how insights are generated, shared, and applied across teams
• Surface market-specific nuances across regions within Canada, helping determine where strategies should be locally tailored and how Canada should be represented within broader global brand decisions

You're excited about this opportunity because you will…

• Synthesize diverse inputs into clear, compelling narratives that drive action
• Own projects end-to-end, from problem definition through to recommendation and impact
• Partner closely with cross-functional teams to shape both the questions being asked and the decisions being made
• Build and refine scalable approaches to insights that increase efficiency and influence across the organization
• Play a key role in ensuring the business is deeply connected to the needs, behaviors, and motivations of its audiences
• Help bring the voice of the Canadian market into broader regional and global conversations, ensuring local audience needs are reflected in how strategy is shaped

We are excited about you because you…

• Are deeply curious about people and motivated to uncover meaningful insights that drive business impact
• Bring a strong strategic mindset, consistently connecting insights to decisions and outcomes
• Communicate with clarity and confidence, with the ability to influence stakeholders and guide discussions
• Are comfortable navigating ambiguity and evolving priorities, while maintaining focus on what matters most
• Demonstrate ownership and accountability, operating independently while collaborating effectively across teams
• Balance analytical rigor with practical judgment, ensuring work is both credible and actionable 
• Experience representing the needs of a market within a broader global organization and connecting local insights to wider business goals

… and have the following experiences

• 5+ years of experience in Marketing Research or Insights
• An understanding of different types of research such as concept development, script testing, copy testing, ethnography, segmentation, brand health, and other qualitative and quantitative techniques
• Comfort with self-moderating 1-on-1 interviews
• Understanding of Qualtrics -or- extensive experience with programming surveys 
• Expertise with brand tracking research - leveraging crosstab tools, stat testing tools, and indexing
• Experience with AI in research with clear understanding of where it can accelerate 
• Experience designing and executing research end-to-end, from scoping through delivery
• Comfort working in fast-paced environments with multiple priorities and stakeholders
• Experience bringing market-specific needs into broader global insights work

The People Team is a global team responsible for helping Asana scale with clarity, focus, and impact. We partner closely with leaders across the company to enable performance, develop talent, and build systems that support strong execution and a great employee experience. Our work spans talent and performance management, rewards, employee relations, people partnerships, and people analytics.

As the People Analytics Partner, you will play a critical role in helping the People Team solve complex problems using data and insights. This role is embedded in People Team initiatives—not operating as a back-office reporting function, but as an active partner on high-priority projects. You’ll work closely with People leaders to analyze challenges, inform decisions, and support execution through clear, actionable analytics.

This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve

• Partner closely with People leaders across Talent, Performance, Rewards, People Partners, and Employee Relations on high-impact projects
• Use analytics to diagnose problems, identify patterns and risks, and evaluate options related to performance, engagement, retention, manager effectiveness, and workforce planning
• Contribute analytics throughout the lifecycle of People projects—from early exploration through execution and follow-up
• Translate data into clear insights and recommendations leaders can act on
• Build dashboards, tools, or models when they directly support decision-making
• Improve data quality, consistency, and usability across People analytics
• Help ensure insights are used to drive focus, prioritization, and follow-through

About you:

• 7+ years of experience as an analytics individual contributor, ideally in People, HR, or organizational analytics
• Strong analytical and problem-solving skills, with comfort working through ambiguity and imperfect data
• Ability to connect quantitative data to real organizational challenges and decisions
• Experience using SQL, spreadsheets, BI tools (e.g., Tableau), and survey data
• Clear communicator who can explain insights and recommendations to non-technical audiences
• Strong project orientation and ability to manage multiple initiatives at once
• Bias toward action and outcomes over analysis for its own sake
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making

At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we’ll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $132,000 - $150,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

#LI-Hybrid

Here at ZoomInfo, we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. If you are a take charge, take initiative, get stuff done individual, we want to talk to you! We have high aspirations for the company and are looking for the right people to help fulfill the dream. We strive to continually improve every aspect of the company and use cutting-edge technologies and processes to delight our customers and rapidly increase revenues.

About the Role

This is a rare opportunity to architect and own ZoomInfo's global Solutions Partner Program from the ground up. As the founding voice of this program, you'll shape how ZoomInfo's consulting and implementation partners deliver, scale, and succeed — directly influencing customer outcomes worldwide.

This is a high-impact individual contributor role with significant visibility and cross-functional influence across ZoomInfo's Partner, Sales, Services, and Executive teams. Reporting to the Sr. AVP of Partnerships, you will work closely with ZoomInfo's Solutions Team to ensure the program is built in alignment with ZoomInfo's overall partner strategy.

If you're a self-starter who thrives on building structure where none exists and wants to make a measurable impact on how ZoomInfo's partners succeed globally — we'd love to hear from you.

What You’ll Do:

• Buld and own ZoomInfo's global Solutions Partner Program, recruiting new partners and establishing the frameworks that drive partner-led implementation quality and customer adoption
• Elevate partners' technical competency and mature their ZoomInfo services practice through structured enablement and repeatable delivery frameworks
• Contribute actively to the evolution of ZoomInfo's broader partner program and go-to-market strategy
• Collect qualitative and quantitative data to measure and report on individual partner performance, ensuring a high standard of implementation quality across top partners
• Drive partner business planning, QBRs, and performance assessments to maintain strategic alignment and accountability
• Own and manage partner interactions across ZoomInfo's internal teams — including Marketing, Product, Pre-Sales, Sales, Services, Enablement, Customer Success, Partner Operations, and Executive Leadership
• Work with the partner team, delivery, and account teams to ensure the proper program elements, resources, and processes are in place to support solutions partners' success
• Serve as a trusted advisor and player/coach to ZoomInfo's solutions partners as the program scales
• Maintain accurate partner records and CRM hygiene across Salesforce and internal tools to ensure operational excellence
• Support partners and internal stakeholders with ad-hoc requests as needed, including legal agreement support, webinars, and collateral development

Core systems and tools: Salesforce, Jira, Confluence, GSuite, Netsuite, Snowflake, GCP, AWS, and additional tools within these ecosystems

What you Bring:

• 5–8 years of experience working with and managing solutions partners in a SaaS environment
• Experience building or scaling a partner program, enablement curriculum, or implementation methodology from an early stage
• Demonstrated success driving partner-sourced or partner-influenced revenue growth
• Existing SI partner relationships and an established network within the ecosystem
• Strong strategic business and marketing planning capabilities
• Excellent interpersonal skills with a proven ability to build positive relationships and influence outcomes through partners
• Proven ability to work cross-functionally across Sales, Services, Product, and Executive stakeholders
• Self-motivated with strong self-management skills and demonstrated leadership qualities as an individual contributor
• Familiarity with SaaS go-to-market motions and the partner ecosystems that support them

What Working at ZoomInfo Brings You:

• Build something that matters: define a program with global reach and lasting impact on how ZoomInfo's partners succeed
• Visibility and influence: Direct access to executive leadership and cross-functional strategy at a market-leading SaaS company
• A culture that is independently driven with a strong team mentality, where your work is recognized and valued
• Competitive compensation and benefits, including a comprehensive package designed to reward high performers
• A clear path to expand your scope and influence within the Partnerships organization as the program scales

About us: 

Built over 20 years ago, ZoomInfo Powered by DiscoverOrg has become the go-to-market standard for over 13,500 companies worldwide. Designed to be the single source of truth, the ZoomInfo platform offers best-in-class technology paired with unrivaled data coverage, accuracy, and depth of contacts, companies, and opportunities essential to empower sales, marketing and recruiting professionals to hit their numbers. Deeply embedded into business workflows and technology stacks-- including integrations with the leading CRM, Sales Engagement, Marketing Automation, and Talent Management applications - ZoomInfo is capable of delivering more predictable, accelerated, and sustainable growth than any stand-alone solution. ZoomInfo’s investors include TA Associates, The Carlyle Group and 22C Capital.

For more information about our leading marketing and sales intelligence solution, visit www.zoominfo.com.

All qualified applicants will receive consideration for employment without regard to race, color, ethnicity, religion, gender, national origin, disability and protected veterans status or any other personal characteristic protected by law

#LI-EB1

#LI-Hybrid

Your role
As an Applied Scientist at Dialpad, you'll be a key driver within our AI team, conducting R&D to power the next generation of autonomous voice agents. While traditional NLP focuses on analyzing static text, your work will center on real-time, multimodal systems that can listen, reason, and take action during live customer interactions. A major focus of the team is advancing DialpadGPT, our proprietary LLM, specifically optimizing it to drive orchestrated agentic workflows and handle complex task execution. Beyond the technical skills, we are a team that values collaboration, continuous learning, and the application of diverse perspectives to solve complex problems. Collaboration will be key as you work alongside our engineering, design, and product teams to build groundbreaking agentic applications.

If you're passionate about agentic and multimodal AI and contributing to a team that's changing the face of business communications, you'll find yourself right at home with us.

This position reports to the Senior Manager of the NLP team and has the opportunity to be based in Vancouver, BC.

What you’ll do

• Research and develop state-of-the-art algorithms for autonomous voice agents, specifically focusing on real-time speech processing and reasoning loops.
• Advance DialpadGPT: Design and execute distributed training strategies to optimize our proprietary LLMs for agentic behaviors, including precise tool use, instruction following, and latency-constrained generation.
• Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts.
• Design and implement orchestration layers that effectively chain LLMs with external tools and APIs to solve complex customer problems autonomously.
• Work with large-scale multimodal datasets (text, audio) to improve model robustness and alignment.
• Collaborate with engineering, product, and design teams to deploy scalable, low-latency models and algorithms in production.
• Submit papers to top-tier academic conferences (ACL, EMNLP, NeurIPS) and contribute to the team’s research culture.

Skills you’ll bring

• Master’s or PhD degree in Computer Science, Machine Learning, Computational Linguistics, or a related quantitative field.
• 2+ years of industry experience in Machine Learning/NLP for Master’s degree holders, or 1+ years for PhD holders.
• Deep understanding of LLMs: Demonstrated experience with training, fine-tuning (PEFT/LoRA), and alignment techniques (RLHF/DPO) for specific domains or tasks.
• Experience with Agentic Systems: Familiarity with building autonomous agents, including concepts like tool use, function calling, reasoning chains (CoT), and memory management.
• Strong proficiency in Python and PyTorch, with the ability to write clean, production-ready research code.
• Research Track Record: A history of publishing in top-tier conferences (ACL, EMNLP, NeurIPS, ICASSP) is highly valued.
• Multimodal Awareness: Familiarity with speech technologies (ASR, TTS) or processing real-time audio streams is a strong plus.
• Ability to bridge the gap between research and product, translating complex technical concepts into business value.
• Familiarity with version control tools like Git for collaborative projects.

As Senior Product Manager for Tokenization, you will own the product strategy and roadmap for Marqeta's tokenization platform - the foundation that powers digital wallet provisioning and network token transactions, and a central pillar of Marqeta's business. You'll shape the strategic direction of the platform, drive innovation that delivers industry-first capabilities, and manage relationships with key partners including Visa, Mastercard, Apple, and Google.

From launching new products and expanding into emerging use cases to ensuring compliance with network and wallet mandates, you'll deliver impactful capabilities across provisioning, transaction processing, and token lifecycle management. Your passion and attention to detail will help keep a mission-critical platform reliable and compliant - while pushing the boundaries of what's possible in tokenization to create lasting value for customers and Marqeta.

We work Flexible First. This role can be performed remotely anywhere within Ontario or British Columbia, Canada. We’d love for you to join us!

This position is for an existing vacancy.

The Impact You’ll Have

• You'll help shape a compelling product vision and roadmap for the tokenization platform, driving alignment and seeking consensus among leadership, engineering, and cross-functional partners
• Directly engage with Visa, Mastercard, Apple, and Google on compliance mandates, protocol migrations, and strategic partnership initiatives - serving as Marqeta's primary product voice for tokenization
• Collaborate across engineering, operations, and international teams to manage complex, multi-month initiatives such as network migrations and regional compliance rollouts
• Translate network and wallet requirements into clear engineering specifications, writing high-quality PRDs with crisp acceptance criteria that maintain engineering velocity
• Deliver customer value iteratively, launching new capabilities end-to-end — from ideation through rollout — driving measurable gains in token provisioning and transaction processing volume
• Identify and flag customer-impacting gaps in the platform, surfacing issues to leadership early with clear status updates and action plans
• Own the product narrative for tokenization across GTM, Product Support, Customer Success, and onboarding  - ensuring cross-functional teams have the product knowledge, documentation, and strategic context they need to move fast and represent the platform accurately to customers
• Collaborate with go-to-market partners to develop product collateral, presentations, and enablement tools that bring tokenization capabilities to customers and prospects
• Stay current with payment industry trends, competitive landscape, and growth opportunities to proactively shape the platform's direction

Who You Are

• 5+ years in a product management role designing and delivering payment solutions that have delighted customers and driven business growth
• Deep expertise in the payment industry ecosystem: card brand regulations, payment networks, tokenization standards, and digital wallet integrations (Apple Pay, Google Pay)
• Proven track record of end-to-end product delivery and execution, with experience independently owning a complex platform with high compliance and reliability requirements
• Strong written and verbal communication skills with a talent for precise articulations of customer problems for technical and business audiences
• Proficient in identifying key metrics, analyzing data, and balancing quantitative and qualitative information to make decisions
• Excellent technical acumen, curiosity, and familiarity with APIs, data analysis, and working alongside engineering teams to shape technically sound solutions
• A customer-centric mindset — you consistently ask "How does this solve the customer's problem?"
• "Roll up your sleeves" mentality to make your products successful and get things done, even when the path is unclear
• Expertise in Agile, stakeholder management, and product lifecycle management

Nice to Haves

• Experience with transaction processing systems, 3DS authentication, or issuer processing platforms
• Familiarity with international payment regulations.
• Experience managing tier-0 or mission-critical services with high uptime expectations
• Understanding of connected platform components beyond tokenization, such as fulfillment, accounts, and issuing systems

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD,  is: 108,000 - 135,000

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

Finance at Brex

The Finance team is a strategic engine at Brex. We lead planning, forecasting, capital allocation, and ROI analysis — partnering across the business to drive clarity and unlock opportunity. We partner across teams at Brex to ensure our business is building and planning with the same dream big goals throughout our entire organization. We’re not here to report on outcomes; we shape them. If you want to influence company direction and think long-term about value creation, this is where your ownership starts. 

Where you’ll work

This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week - Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

What you’ll do

We are hiring two Finance Associates who will each initially own distinct workstreams before rotating responsibilities — building deep expertise across the full Corporate FP&A function. Your work will directly inform Brex's total company business plan and executive reporting, giving you real exposure and ownership from day one. You will also be a core contributor to our AI-first initiatives and financial systems roadmap — we are looking for someone who sees AI not as an occasional tool, but as the default lens through which they approach every workflow.

Responsibilities

Financial Planning & Modeling

• Own our forecasting & planning process, managing our operational model and collaborating with stakeholders to make recommendations that drive the business forward
• Review, evaluate, maintain, and improve financial models used for OKRs and operational & financial reporting
• Participate in budgeting, forecasting, headcount planning, and G&A finance processes

Management Reporting & Performance

• Own our monthly management reporting and bi-weekly rolling forecast process delivered directly to our executive leadership team
• Support Finance Business Partners with the creation of Budget vs. Actuals materials

Shared Across Both Workstreams

• Build out and maintain Finance AI tooling and financial systems infrastructure, identifying opportunities to automate reporting and scale the team's impact
• Contribute to special projects and ad hoc analyses supporting senior leadership

Requirements

• Bachelor’s Degree in Economics, Finance, Business, or related field
• 2+ years of Strategic Finance, FP&A, or Investment Banking experience
• An AI-first mindset: you default to asking how AI can improve every workflow, you actively experiment with new tools, and you have used AI to accelerate analysis or automate a task
• Mastery of Excel and PowerPoint with proven experience in building financial models and managing complex data 
• Strong communication, team-working, quantitative and analytical skills
• Intellectual curiosity, a collaborative work style, and the drive to take ownership in a fast-moving environment
• Comfort managing multiple workstreams simultaneously and proactively driving work forward without being asked
• A bias toward proactive insight over reactive reporting
• Ability to operate independently, build structure in ambiguous environments, and prioritize effectively

Compensation

The expected salary range for this role is $104,000-$117,000 CAD. However, the starting base pay will depend on a number of factors, including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Strong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage
• Insurance coverage (life, short-term disability, long-term disability, and more)
• Health Care Spending Account
• Two different Employee Assistance Programs
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

Note: Benefits may vary by location and are subject to local regulations.

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Vancouver_Canada

About the Role

ZoomInfo is seeking a Senior Data Systems Analyst to become the expert on our company data pipeline—the system that ingests, processes, and profiles millions of company records that power our customers' go-to-market strategies.

In this role, you'll build deep expertise in how our company data flows from acquisition through profiling and output. You'll read code to understand data transformations and system dependencies, bring informed opinions to design conversations with Engineering and Product, and help shape the evolution of our next-generation data infrastructure. As you build mastery of our systems, you'll increasingly lead strategic data improvement initiatives that require both systems thinking and creative problem-solving.

This isn't about building dashboards or SQL reports. This is about understanding data systems at an architectural level, solving ambiguous data challenges, and ensuring our pipeline infrastructure continuously evolves to meet customer needs and maintain competitive advantage.

You'll work closely with other data analysts during an active infrastructure transition period, and as systems stabilize and your expertise deepens, you'll progressively own more of the pipeline architecture and strategic initiatives. This is a role with significant growth runway for someone who wants to become the go-to technical expert on company data systems.

Who You Are

Systems Thinker with Technical Depth: You understand how data systems work, not just what they produce. You've worked with data pipelines, ETL systems, or data processing infrastructure—maybe you've improved one, debugged one, or owned components of one. You can read code (Python, Java, SQL, or similar) well enough to understand data transformations and trace how data flows through systems.

Opinionated Technical Contributor: You don't just execute—you have informed opinions on how things should work. You can assess technical tradeoffs, evaluate whether a proposed solution is feasible, and contribute meaningfully to design conversations with engineers. You're comfortable saying "here's what I think and why" based on your technical understanding.

Growth-Oriented Problem Solver: You're excited to build deep expertise in a complex domain and grow into leading strategic initiatives. You've tackled ambiguous problems that required figuring things out as you went, and you want to expand your project leadership capabilities in a systems-focused environment.

Analytical and Hands-On: You're equally comfortable writing code to analyze data patterns and manually investigating edge cases to understand what's really happening. You dig into details when needed and know when to zoom out to see the bigger picture.

Clear Communicator: You can explain technical complexity to non-technical audiences. You've worked effectively with Engineering, Product, or cross-functional teams, translating between technical constraints and business needs.

Comfortable with Ambiguity: You thrive in evolving environments where priorities shift and problems aren't always well-defined. You maintain momentum and quality even when the path forward isn't perfectly clear.

What You'll Do

In your first 6-12 months, your primary focus will be building deep expertise in our pipeline architecture and contributing to our infrastructure transition. You'll work alongside other analysts who have context on our systems, learning the architecture while bringing fresh perspectives and technical depth. As you gain mastery and systems stabilize, you'll increasingly own pipeline architecture decisions and lead strategic data improvement initiatives.

Build Deep Pipeline & Systems Expertise

• Master our company data pipeline architecture—how data flows from ingestion through profiling, what transforms are applied at each stage, and how components interconnect
• Read and analyze production code to understand data transformations, trace data lineage, and assess how proposed changes would impact the system
• Develop frameworks for evaluating tradeoffs between technical complexity, implementation effort, and customer impact
• Create clear documentation, system maps, and knowledge resources that capture architecture decisions, dependencies, and design rationale

Contribute to Pipeline Evolution & Infrastructure Improvements

• Participate actively in design conversations with Engineering and Product about our next-generation pipeline, bringing data quality insights, technical feasibility assessments, and informed opinions on architectural decisions
• Help validate pipeline improvements through rigorous testing, impact analysis, and hands-on verification of data quality
• Translate data quality investigations and emerging requirements into system-level improvement opportunities
• Collaborate with team members to determine when problems should be solved at the pipeline/profiler level versus through downstream approaches

Solve Complex, Ambiguous Data Challenges

• Lead or contribute to data improvement initiatives that require both systems thinking and creative problem-solving—such as improving location verification across international markets, integrating new data sources, or solving novel data extraction challenges
• Tackle problems where the solution isn't obvious through a blend of code analysis, manual investigation, cross-functional coordination, and iterative problem-solving
• Build and apply repeatable approaches to testing, validation, and root cause analysis

Build Partnerships & Institutional Knowledge

• Develop strong working relationships with Data Acquisition, Product, Engineering, and fellow data analysts
• Conduct impact analyses and validation studies to ensure proposed changes deliver intended outcomes
• Document your learning, approaches, and insights so knowledge is shared and institutional memory builds across the team
• Serve as a technical resource as you develop expertise, helping bridge immediate data quality needs with long-term pipeline capabilities

What You'll Bring

Required

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field
• 5+ years of experience in data analytics, data engineering, or related technical roles
• Experience working with data pipelines, ETL systems, or data processing infrastructure—you understand how data moves through systems and what can go wrong
• Ability to read and understand code (Python, Java, SQL, or similar) to analyze data transformations, understand system logic, and assess technical feasibility
• Strong programming skills in Python and SQL for data analysis and manipulation
• Experience solving ambiguous, multi-faceted data problems that required figuring out the approach, not just executing a well-defined analysis
• Demonstrated ability to work effectively with Engineering and/or Product teams, translating between technical implementation and business/customer needs
• Strong analytical skills with ability to investigate complex issues systematically
• Excellent communication skills—able to explain technical concepts clearly to diverse audiences
• Self-directed with strong ownership mentality—you drive your work forward and know when to seek input

Strongly Preferred

• Experience with company data, business data, web data acquisition, or data quality initiatives
• Experience with data profiling, entity resolution, record linkage, or data matching systems
• Background contributing to system design discussions or technical architecture decisions
• Experience creating technical documentation or knowledge-sharing resources
• Knowledge of web data structures (HTML/DOM), data extraction, or data collection systems
• Experience designing validation strategies or testing frameworks
• Track record of leading or co-leading cross-functional data projects

This Role Is Not a Fit If:

You're looking to focus primarily on business analytics, building dashboards, creating reports, or analyzing business metrics. While you'll do analysis in this role, the core mission is understanding and improving data systems architecture.

This Role Is a Strong Fit If:

You want to become the expert on how data systems work and grow into leading strategic initiatives. You're excited to build deep technical expertise, contribute informed opinions to design decisions, and progressively take on more ownership as you master the domain. You enjoy solving problems where the answer isn't obvious and seeing your work directly improve product capabilities.

#LI-JH1

#LI-Hybrid

About the Role

ZoomInfo is seeking a Senior Data Systems Analyst to become the expert on our company data pipeline—the system that ingests, processes, and profiles millions of company records that power our customers' go-to-market strategies.

In this role, you'll build deep expertise in how our company data flows from acquisition through profiling and output. You'll read code to understand data transformations and system dependencies, bring informed opinions to design conversations with Engineering and Product, and help shape the evolution of our next-generation data infrastructure. As you build mastery of our systems, you'll increasingly lead strategic data improvement initiatives that require both systems thinking and creative problem-solving.

This isn't about building dashboards or SQL reports. This is about understanding data systems at an architectural level, solving ambiguous data challenges, and ensuring our pipeline infrastructure continuously evolves to meet customer needs and maintain competitive advantage.

You'll work closely with other data analysts during an active infrastructure transition period, and as systems stabilize and your expertise deepens, you'll progressively own more of the pipeline architecture and strategic initiatives. This is a role with significant growth runway for someone who wants to become the go-to technical expert on company data systems.

Who You Are

Systems Thinker with Technical Depth: You understand how data systems work, not just what they produce. You've worked with data pipelines, ETL systems, or data processing infrastructure—maybe you've improved one, debugged one, or owned components of one. You can read code (Python, Java, SQL, or similar) well enough to understand data transformations and trace how data flows through systems.

Opinionated Technical Contributor: You don't just execute—you have informed opinions on how things should work. You can assess technical tradeoffs, evaluate whether a proposed solution is feasible, and contribute meaningfully to design conversations with engineers. You're comfortable saying "here's what I think and why" based on your technical understanding.

Growth-Oriented Problem Solver: You're excited to build deep expertise in a complex domain and grow into leading strategic initiatives. You've tackled ambiguous problems that required figuring things out as you went, and you want to expand your project leadership capabilities in a systems-focused environment.

Analytical and Hands-On: You're equally comfortable writing code to analyze data patterns and manually investigating edge cases to understand what's really happening. You dig into details when needed and know when to zoom out to see the bigger picture.

Clear Communicator: You can explain technical complexity to non-technical audiences. You've worked effectively with Engineering, Product, or cross-functional teams, translating between technical constraints and business needs.

Comfortable with Ambiguity: You thrive in evolving environments where priorities shift and problems aren't always well-defined. You maintain momentum and quality even when the path forward isn't perfectly clear.

What You'll Do

In your first 6-12 months, your primary focus will be building deep expertise in our pipeline architecture and contributing to our infrastructure transition. You'll work alongside other analysts who have context on our systems, learning the architecture while bringing fresh perspectives and technical depth. As you gain mastery and systems stabilize, you'll increasingly own pipeline architecture decisions and lead strategic data improvement initiatives.

Build Deep Pipeline & Systems Expertise

• Master our company data pipeline architecture—how data flows from ingestion through profiling, what transforms are applied at each stage, and how components interconnect
• Read and analyze production code to understand data transformations, trace data lineage, and assess how proposed changes would impact the system
• Develop frameworks for evaluating tradeoffs between technical complexity, implementation effort, and customer impact
• Create clear documentation, system maps, and knowledge resources that capture architecture decisions, dependencies, and design rationale

Contribute to Pipeline Evolution & Infrastructure Improvements

• Participate actively in design conversations with Engineering and Product about our next-generation pipeline, bringing data quality insights, technical feasibility assessments, and informed opinions on architectural decisions
• Help validate pipeline improvements through rigorous testing, impact analysis, and hands-on verification of data quality
• Translate data quality investigations and emerging requirements into system-level improvement opportunities
• Collaborate with team members to determine when problems should be solved at the pipeline/profiler level versus through downstream approaches

Solve Complex, Ambiguous Data Challenges

• Lead or contribute to data improvement initiatives that require both systems thinking and creative problem-solving—such as improving location verification across international markets, integrating new data sources, or solving novel data extraction challenges
• Tackle problems where the solution isn't obvious through a blend of code analysis, manual investigation, cross-functional coordination, and iterative problem-solving
• Build and apply repeatable approaches to testing, validation, and root cause analysis

Build Partnerships & Institutional Knowledge

• Develop strong working relationships with Data Acquisition, Product, Engineering, and fellow data analysts
• Conduct impact analyses and validation studies to ensure proposed changes deliver intended outcomes
• Document your learning, approaches, and insights so knowledge is shared and institutional memory builds across the team
• Serve as a technical resource as you develop expertise, helping bridge immediate data quality needs with long-term pipeline capabilities

What You'll Bring

Required

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field
• 5+ years of experience in data analytics, data engineering, or related technical roles
• Experience working with data pipelines, ETL systems, or data processing infrastructure—you understand how data moves through systems and what can go wrong
• Ability to read and understand code (Python, Java, SQL, or similar) to analyze data transformations, understand system logic, and assess technical feasibility
• Strong programming skills in Python and SQL for data analysis and manipulation
• Experience solving ambiguous, multi-faceted data problems that required figuring out the approach, not just executing a well-defined analysis
• Demonstrated ability to work effectively with Engineering and/or Product teams, translating between technical implementation and business/customer needs
• Strong analytical skills with ability to investigate complex issues systematically
• Excellent communication skills—able to explain technical concepts clearly to diverse audiences
• Self-directed with strong ownership mentality—you drive your work forward and know when to seek input

Strongly Preferred

• Experience with company data, business data, web data acquisition, or data quality initiatives
• Experience with data profiling, entity resolution, record linkage, or data matching systems
• Background contributing to system design discussions or technical architecture decisions
• Experience creating technical documentation or knowledge-sharing resources
• Knowledge of web data structures (HTML/DOM), data extraction, or data collection systems
• Experience designing validation strategies or testing frameworks
• Track record of leading or co-leading cross-functional data projects

This Role Is Not a Fit If:

You're looking to focus primarily on business analytics, building dashboards, creating reports, or analyzing business metrics. While you'll do analysis in this role, the core mission is understanding and improving data systems architecture.

This Role Is a Strong Fit If:

You want to become the expert on how data systems work and grow into leading strategic initiatives. You're excited to build deep technical expertise, contribute informed opinions to design decisions, and progressively take on more ownership as you master the domain. You enjoy solving problems where the answer isn't obvious and seeing your work directly improve product capabilities.

#LI-JH1

#LI-Hybrid

About the Role

ZoomInfo is seeking a Senior Data Systems Analyst to become the expert on our company data pipeline—the system that ingests, processes, and profiles millions of company records that power our customers' go-to-market strategies.

In this role, you'll build deep expertise in how our company data flows from acquisition through profiling and output. You'll read code to understand data transformations and system dependencies, bring informed opinions to design conversations with Engineering and Product, and help shape the evolution of our next-generation data infrastructure. As you build mastery of our systems, you'll increasingly lead strategic data improvement initiatives that require both systems thinking and creative problem-solving.

This isn't about building dashboards or SQL reports. This is about understanding data systems at an architectural level, solving ambiguous data challenges, and ensuring our pipeline infrastructure continuously evolves to meet customer needs and maintain competitive advantage.

You'll work closely with other data analysts during an active infrastructure transition period, and as systems stabilize and your expertise deepens, you'll progressively own more of the pipeline architecture and strategic initiatives. This is a role with significant growth runway for someone who wants to become the go-to technical expert on company data systems.

Who You Are

Systems Thinker with Technical Depth: You understand how data systems work, not just what they produce. You've worked with data pipelines, ETL systems, or data processing infrastructure—maybe you've improved one, debugged one, or owned components of one. You can read code (Python, Java, SQL, or similar) well enough to understand data transformations and trace how data flows through systems.

Opinionated Technical Contributor: You don't just execute—you have informed opinions on how things should work. You can assess technical tradeoffs, evaluate whether a proposed solution is feasible, and contribute meaningfully to design conversations with engineers. You're comfortable saying "here's what I think and why" based on your technical understanding.

Growth-Oriented Problem Solver: You're excited to build deep expertise in a complex domain and grow into leading strategic initiatives. You've tackled ambiguous problems that required figuring things out as you went, and you want to expand your project leadership capabilities in a systems-focused environment.

Analytical and Hands-On: You're equally comfortable writing code to analyze data patterns and manually investigating edge cases to understand what's really happening. You dig into details when needed and know when to zoom out to see the bigger picture.

Clear Communicator: You can explain technical complexity to non-technical audiences. You've worked effectively with Engineering, Product, or cross-functional teams, translating between technical constraints and business needs.

Comfortable with Ambiguity: You thrive in evolving environments where priorities shift and problems aren't always well-defined. You maintain momentum and quality even when the path forward isn't perfectly clear.

What You'll Do

In your first 6-12 months, your primary focus will be building deep expertise in our pipeline architecture and contributing to our infrastructure transition. You'll work alongside other analysts who have context on our systems, learning the architecture while bringing fresh perspectives and technical depth. As you gain mastery and systems stabilize, you'll increasingly own pipeline architecture decisions and lead strategic data improvement initiatives.

Build Deep Pipeline & Systems Expertise

• Master our company data pipeline architecture—how data flows from ingestion through profiling, what transforms are applied at each stage, and how components interconnect
• Read and analyze production code to understand data transformations, trace data lineage, and assess how proposed changes would impact the system
• Develop frameworks for evaluating tradeoffs between technical complexity, implementation effort, and customer impact
• Create clear documentation, system maps, and knowledge resources that capture architecture decisions, dependencies, and design rationale

Contribute to Pipeline Evolution & Infrastructure Improvements

• Participate actively in design conversations with Engineering and Product about our next-generation pipeline, bringing data quality insights, technical feasibility assessments, and informed opinions on architectural decisions
• Help validate pipeline improvements through rigorous testing, impact analysis, and hands-on verification of data quality
• Translate data quality investigations and emerging requirements into system-level improvement opportunities
• Collaborate with team members to determine when problems should be solved at the pipeline/profiler level versus through downstream approaches

Solve Complex, Ambiguous Data Challenges

• Lead or contribute to data improvement initiatives that require both systems thinking and creative problem-solving—such as improving location verification across international markets, integrating new data sources, or solving novel data extraction challenges
• Tackle problems where the solution isn't obvious through a blend of code analysis, manual investigation, cross-functional coordination, and iterative problem-solving
• Build and apply repeatable approaches to testing, validation, and root cause analysis

Build Partnerships & Institutional Knowledge

• Develop strong working relationships with Data Acquisition, Product, Engineering, and fellow data analysts
• Conduct impact analyses and validation studies to ensure proposed changes deliver intended outcomes
• Document your learning, approaches, and insights so knowledge is shared and institutional memory builds across the team
• Serve as a technical resource as you develop expertise, helping bridge immediate data quality needs with long-term pipeline capabilities

What You'll Bring

Required

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field
• 5+ years of experience in data analytics, data engineering, or related technical roles
• Experience working with data pipelines, ETL systems, or data processing infrastructure—you understand how data moves through systems and what can go wrong
• Ability to read and understand code (Python, Java, SQL, or similar) to analyze data transformations, understand system logic, and assess technical feasibility
• Strong programming skills in Python and SQL for data analysis and manipulation
• Experience solving ambiguous, multi-faceted data problems that required figuring out the approach, not just executing a well-defined analysis
• Demonstrated ability to work effectively with Engineering and/or Product teams, translating between technical implementation and business/customer needs
• Strong analytical skills with ability to investigate complex issues systematically
• Excellent communication skills—able to explain technical concepts clearly to diverse audiences
• Self-directed with strong ownership mentality—you drive your work forward and know when to seek input

Strongly Preferred

• Experience with company data, business data, web data acquisition, or data quality initiatives
• Experience with data profiling, entity resolution, record linkage, or data matching systems
• Background contributing to system design discussions or technical architecture decisions
• Experience creating technical documentation or knowledge-sharing resources
• Knowledge of web data structures (HTML/DOM), data extraction, or data collection systems
• Experience designing validation strategies or testing frameworks
• Track record of leading or co-leading cross-functional data projects

This Role Is Not a Fit If:

You're looking to focus primarily on business analytics, building dashboards, creating reports, or analyzing business metrics. While you'll do analysis in this role, the core mission is understanding and improving data systems architecture.

This Role Is a Strong Fit If:

You want to become the expert on how data systems work and grow into leading strategic initiatives. You're excited to build deep technical expertise, contribute informed opinions to design decisions, and progressively take on more ownership as you master the domain. You enjoy solving problems where the answer isn't obvious and seeing your work directly improve product capabilities.

#LI-JH1

#LI-Hybrid

About the Role

ZoomInfo is seeking a Senior Data Systems Analyst to become the expert on our company data pipeline—the system that ingests, processes, and profiles millions of company records that power our customers' go-to-market strategies.

In this role, you'll build deep expertise in how our company data flows from acquisition through profiling and output. You'll read code to understand data transformations and system dependencies, bring informed opinions to design conversations with Engineering and Product, and help shape the evolution of our next-generation data infrastructure. As you build mastery of our systems, you'll increasingly lead strategic data improvement initiatives that require both systems thinking and creative problem-solving.

This isn't about building dashboards or SQL reports. This is about understanding data systems at an architectural level, solving ambiguous data challenges, and ensuring our pipeline infrastructure continuously evolves to meet customer needs and maintain competitive advantage.

You'll work closely with other data analysts during an active infrastructure transition period, and as systems stabilize and your expertise deepens, you'll progressively own more of the pipeline architecture and strategic initiatives. This is a role with significant growth runway for someone who wants to become the go-to technical expert on company data systems.

Who You Are

Systems Thinker with Technical Depth: You understand how data systems work, not just what they produce. You've worked with data pipelines, ETL systems, or data processing infrastructure—maybe you've improved one, debugged one, or owned components of one. You can read code (Python, Java, SQL, or similar) well enough to understand data transformations and trace how data flows through systems.

Opinionated Technical Contributor: You don't just execute—you have informed opinions on how things should work. You can assess technical tradeoffs, evaluate whether a proposed solution is feasible, and contribute meaningfully to design conversations with engineers. You're comfortable saying "here's what I think and why" based on your technical understanding.

Growth-Oriented Problem Solver: You're excited to build deep expertise in a complex domain and grow into leading strategic initiatives. You've tackled ambiguous problems that required figuring things out as you went, and you want to expand your project leadership capabilities in a systems-focused environment.

Analytical and Hands-On: You're equally comfortable writing code to analyze data patterns and manually investigating edge cases to understand what's really happening. You dig into details when needed and know when to zoom out to see the bigger picture.

Clear Communicator: You can explain technical complexity to non-technical audiences. You've worked effectively with Engineering, Product, or cross-functional teams, translating between technical constraints and business needs.

Comfortable with Ambiguity: You thrive in evolving environments where priorities shift and problems aren't always well-defined. You maintain momentum and quality even when the path forward isn't perfectly clear.

What You'll Do

In your first 6-12 months, your primary focus will be building deep expertise in our pipeline architecture and contributing to our infrastructure transition. You'll work alongside other analysts who have context on our systems, learning the architecture while bringing fresh perspectives and technical depth. As you gain mastery and systems stabilize, you'll increasingly own pipeline architecture decisions and lead strategic data improvement initiatives.

Build Deep Pipeline & Systems Expertise

• Master our company data pipeline architecture—how data flows from ingestion through profiling, what transforms are applied at each stage, and how components interconnect
• Read and analyze production code to understand data transformations, trace data lineage, and assess how proposed changes would impact the system
• Develop frameworks for evaluating tradeoffs between technical complexity, implementation effort, and customer impact
• Create clear documentation, system maps, and knowledge resources that capture architecture decisions, dependencies, and design rationale

Contribute to Pipeline Evolution & Infrastructure Improvements

• Participate actively in design conversations with Engineering and Product about our next-generation pipeline, bringing data quality insights, technical feasibility assessments, and informed opinions on architectural decisions
• Help validate pipeline improvements through rigorous testing, impact analysis, and hands-on verification of data quality
• Translate data quality investigations and emerging requirements into system-level improvement opportunities
• Collaborate with team members to determine when problems should be solved at the pipeline/profiler level versus through downstream approaches

Solve Complex, Ambiguous Data Challenges

• Lead or contribute to data improvement initiatives that require both systems thinking and creative problem-solving—such as improving location verification across international markets, integrating new data sources, or solving novel data extraction challenges
• Tackle problems where the solution isn't obvious through a blend of code analysis, manual investigation, cross-functional coordination, and iterative problem-solving
• Build and apply repeatable approaches to testing, validation, and root cause analysis

Build Partnerships & Institutional Knowledge

• Develop strong working relationships with Data Acquisition, Product, Engineering, and fellow data analysts
• Conduct impact analyses and validation studies to ensure proposed changes deliver intended outcomes
• Document your learning, approaches, and insights so knowledge is shared and institutional memory builds across the team
• Serve as a technical resource as you develop expertise, helping bridge immediate data quality needs with long-term pipeline capabilities

What You'll Bring

Required

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field
• 5+ years of experience in data analytics, data engineering, or related technical roles
• Experience working with data pipelines, ETL systems, or data processing infrastructure—you understand how data moves through systems and what can go wrong
• Ability to read and understand code (Python, Java, SQL, or similar) to analyze data transformations, understand system logic, and assess technical feasibility
• Strong programming skills in Python and SQL for data analysis and manipulation
• Experience solving ambiguous, multi-faceted data problems that required figuring out the approach, not just executing a well-defined analysis
• Demonstrated ability to work effectively with Engineering and/or Product teams, translating between technical implementation and business/customer needs
• Strong analytical skills with ability to investigate complex issues systematically
• Excellent communication skills—able to explain technical concepts clearly to diverse audiences
• Self-directed with strong ownership mentality—you drive your work forward and know when to seek input

Strongly Preferred

• Experience with company data, business data, web data acquisition, or data quality initiatives
• Experience with data profiling, entity resolution, record linkage, or data matching systems
• Background contributing to system design discussions or technical architecture decisions
• Experience creating technical documentation or knowledge-sharing resources
• Knowledge of web data structures (HTML/DOM), data extraction, or data collection systems
• Experience designing validation strategies or testing frameworks
• Track record of leading or co-leading cross-functional data projects

This Role Is Not a Fit If:

You're looking to focus primarily on business analytics, building dashboards, creating reports, or analyzing business metrics. While you'll do analysis in this role, the core mission is understanding and improving data systems architecture.

This Role Is a Strong Fit If:

You want to become the expert on how data systems work and grow into leading strategic initiatives. You're excited to build deep technical expertise, contribute informed opinions to design decisions, and progressively take on more ownership as you master the domain. You enjoy solving problems where the answer isn't obvious and seeing your work directly improve product capabilities.

#LI-JH1

#LI-Hybrid

About the Role

ZoomInfo is seeking a Senior Data Systems Analyst to become the expert on our company data pipeline—the system that ingests, processes, and profiles millions of company records that power our customers' go-to-market strategies.

In this role, you'll build deep expertise in how our company data flows from acquisition through profiling and output. You'll read code to understand data transformations and system dependencies, bring informed opinions to design conversations with Engineering and Product, and help shape the evolution of our next-generation data infrastructure. As you build mastery of our systems, you'll increasingly lead strategic data improvement initiatives that require both systems thinking and creative problem-solving.

This isn't about building dashboards or SQL reports. This is about understanding data systems at an architectural level, solving ambiguous data challenges, and ensuring our pipeline infrastructure continuously evolves to meet customer needs and maintain competitive advantage.

You'll work closely with other data analysts during an active infrastructure transition period, and as systems stabilize and your expertise deepens, you'll progressively own more of the pipeline architecture and strategic initiatives. This is a role with significant growth runway for someone who wants to become the go-to technical expert on company data systems.

Who You Are

Systems Thinker with Technical Depth: You understand how data systems work, not just what they produce. You've worked with data pipelines, ETL systems, or data processing infrastructure—maybe you've improved one, debugged one, or owned components of one. You can read code (Python, Java, SQL, or similar) well enough to understand data transformations and trace how data flows through systems.

Opinionated Technical Contributor: You don't just execute—you have informed opinions on how things should work. You can assess technical tradeoffs, evaluate whether a proposed solution is feasible, and contribute meaningfully to design conversations with engineers. You're comfortable saying "here's what I think and why" based on your technical understanding.

Growth-Oriented Problem Solver: You're excited to build deep expertise in a complex domain and grow into leading strategic initiatives. You've tackled ambiguous problems that required figuring things out as you went, and you want to expand your project leadership capabilities in a systems-focused environment.

Analytical and Hands-On: You're equally comfortable writing code to analyze data patterns and manually investigating edge cases to understand what's really happening. You dig into details when needed and know when to zoom out to see the bigger picture.

Clear Communicator: You can explain technical complexity to non-technical audiences. You've worked effectively with Engineering, Product, or cross-functional teams, translating between technical constraints and business needs.

Comfortable with Ambiguity: You thrive in evolving environments where priorities shift and problems aren't always well-defined. You maintain momentum and quality even when the path forward isn't perfectly clear.

What You'll Do

In your first 6-12 months, your primary focus will be building deep expertise in our pipeline architecture and contributing to our infrastructure transition. You'll work alongside other analysts who have context on our systems, learning the architecture while bringing fresh perspectives and technical depth. As you gain mastery and systems stabilize, you'll increasingly own pipeline architecture decisions and lead strategic data improvement initiatives.

Build Deep Pipeline & Systems Expertise

• Master our company data pipeline architecture—how data flows from ingestion through profiling, what transforms are applied at each stage, and how components interconnect
• Read and analyze production code to understand data transformations, trace data lineage, and assess how proposed changes would impact the system
• Develop frameworks for evaluating tradeoffs between technical complexity, implementation effort, and customer impact
• Create clear documentation, system maps, and knowledge resources that capture architecture decisions, dependencies, and design rationale

Contribute to Pipeline Evolution & Infrastructure Improvements

• Participate actively in design conversations with Engineering and Product about our next-generation pipeline, bringing data quality insights, technical feasibility assessments, and informed opinions on architectural decisions
• Help validate pipeline improvements through rigorous testing, impact analysis, and hands-on verification of data quality
• Translate data quality investigations and emerging requirements into system-level improvement opportunities
• Collaborate with team members to determine when problems should be solved at the pipeline/profiler level versus through downstream approaches

Solve Complex, Ambiguous Data Challenges

• Lead or contribute to data improvement initiatives that require both systems thinking and creative problem-solving—such as improving location verification across international markets, integrating new data sources, or solving novel data extraction challenges
• Tackle problems where the solution isn't obvious through a blend of code analysis, manual investigation, cross-functional coordination, and iterative problem-solving
• Build and apply repeatable approaches to testing, validation, and root cause analysis

Build Partnerships & Institutional Knowledge

• Develop strong working relationships with Data Acquisition, Product, Engineering, and fellow data analysts
• Conduct impact analyses and validation studies to ensure proposed changes deliver intended outcomes
• Document your learning, approaches, and insights so knowledge is shared and institutional memory builds across the team
• Serve as a technical resource as you develop expertise, helping bridge immediate data quality needs with long-term pipeline capabilities

What You'll Bring

Required

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field
• 5+ years of experience in data analytics, data engineering, or related technical roles
• Experience working with data pipelines, ETL systems, or data processing infrastructure—you understand how data moves through systems and what can go wrong
• Ability to read and understand code (Python, Java, SQL, or similar) to analyze data transformations, understand system logic, and assess technical feasibility
• Strong programming skills in Python and SQL for data analysis and manipulation
• Experience solving ambiguous, multi-faceted data problems that required figuring out the approach, not just executing a well-defined analysis
• Demonstrated ability to work effectively with Engineering and/or Product teams, translating between technical implementation and business/customer needs
• Strong analytical skills with ability to investigate complex issues systematically
• Excellent communication skills—able to explain technical concepts clearly to diverse audiences
• Self-directed with strong ownership mentality—you drive your work forward and know when to seek input

Strongly Preferred

• Experience with company data, business data, web data acquisition, or data quality initiatives
• Experience with data profiling, entity resolution, record linkage, or data matching systems
• Background contributing to system design discussions or technical architecture decisions
• Experience creating technical documentation or knowledge-sharing resources
• Knowledge of web data structures (HTML/DOM), data extraction, or data collection systems
• Experience designing validation strategies or testing frameworks
• Track record of leading or co-leading cross-functional data projects

This Role Is Not a Fit If:

You're looking to focus primarily on business analytics, building dashboards, creating reports, or analyzing business metrics. While you'll do analysis in this role, the core mission is understanding and improving data systems architecture.

This Role Is a Strong Fit If:

You want to become the expert on how data systems work and grow into leading strategic initiatives. You're excited to build deep technical expertise, contribute informed opinions to design decisions, and progressively take on more ownership as you master the domain. You enjoy solving problems where the answer isn't obvious and seeing your work directly improve product capabilities.

#LI-JH1

#LI-Hybrid

Product Manager - Computer Vision & Data Products (Canada, Remote)

Events in recent years have made us all too familiar with the havoc that natural disasters can wreak, and the increasing frequency and intensity with which they are occurring. Despite record levels of losses, conventional methods of identifying and managing risk continue to provide an incomplete solution to these threats.

ZestyAI uses novel data gathering and machine learning approaches to produce higher quality information about the risks to property from catastrophes like severe convective storms and wildfires. While AI alone may not be able to thwart these disasters, it can help communities around the world become more prepared for them, and ultimately that will lead to better outcomes for business and society.

As a Product Manager - Computer Vision and Data Products, you are an analytical thinker and passionate about working with complex data. You are a pacesetter who wants to deliver innovative products; you are organized, self-directed, committed to innovation, and possess outstanding EQ and communication skills. You will be crucial in operating the ZestyAI platform and delivering property characteristics and risk information to our clients. You thrive in a collaborative and creative environment that moves fast and are comfortable learning new skills, leveraging the latest AI tools, and working with unfamiliar technologies.

The Opportunity:

• Own the product and feature development lifecycle from inception to launch in the field of machine learning, large language models, and computer vision
• Build the analytics and model development roadmap of data and risk solutions by researching and analyzing various sources of information
• Discover and translate data into tractable data science questions and engineering specifications to guide strategic decision making
• Work closely with data scientists and software engineers as a key member of the product development team
• Act as the model owner and subject matter expert when interfacing with Regulators and Customers
• Iterate rapidly on everything; all of the above happens in a fast-paced business-driven environment that you must be comfortable with
• Work with our customers to understand complex workflows and pain points and find solutions to the problems

What You Bring to the ZestyAI Team:

• 3-6 years of work experience in analytics, data science, financial modeling, risk modeling, climate modeling or other relevant field

○  Including 1-2 years of Product Management experience, working with data products or model-based features such as actuarial risk model, climate risk model, credit risk model, search model, etc.

• Bachelor's or Master's in a quantitative field such as Engineering, Sciences, Commerce
• Outstanding communication skills, well-versed in building executive-style presentations
• Ability to manage multiple/competing priorities and deliver on time
• Comfortable leveraging AI tools to automate and accelerate everyday work (i.e. Claude Cowork)
• Proficient in SQL, Excel, Python
• Must be legally eligible to work in Canada

Nice to Have:

• Exposure to insurance, real estate, and risk modeling
• Experience working with computer vision models

Why ZestyAI:

• Be a part of a well-funded growth-stage start-up
• Work with a high-performance product team and cutting-edge development team
• Market competitive comp and equity incentives to give you a stake in our future
• Remote-first policy
• Flexible Time Off
• Comprehensive benefits package
• Home office setup stipend
• Annual Learning and Development allowance
• An upbeat and collaborative work culture
• Company-sponsored outings and offsites

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

Most AI research today is shaped by the constraints of existing hardware. This role starts from the other direction: what would you build if the architecture let you rethink the fundamentals? You will design and develop AI models and training methodologies on wafer-scale hardware, working at the level of optimization theory, model architecture, and statistical foundations rather than assembling existing components. 

The ATG sits at the intersection of AI, computational science, and computer architecture, and your work will draw on all three. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories. 

What You Will Do 

• Design AI models and training methods from first principles, leveraging architectural properties of wafer-scale hardware that are unavailable on conventional platforms. 
• Investigate how techniques from computational science—numerical methods, PDE solvers, simulation—can inform and advance AI model design, and explore hybrid workflows that couple simulation and learning. 
• Develop a deep understanding of the hardware substrate and use it to guide algorithmic choices: model structure, optimization strategy, memory access patterns, numerical precision. 
• Publish findings and present at top-tier venues (NeurIPS, ICML, ICLR, etc.); represent Cerebras in the broader AI/ML research community. 
• Inform the design of future Cerebras hardware and software by identifying the computational patterns that matter most for next-generation AI workloads. 

What We Are Looking For 

• PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field preferred; exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Mathematical maturity: comfort with the theory behind gradient methods, loss landscapes, generalization, and the relationship between model structure and data statistics. 
• Track record of published research at top-tier AI or computational science venues. 
• Proficiency in Python and PyTorch; comfort with C or other low-level languages is a strong signal. 
• Excellent communication and interpersonal skills: able to present complex technical material to both ML and systems audiences, and to collaborate effectively in a fast-paced, small-team environment. 

Why This Opportunity Is Exciting And Unique 

• You will have direct access to hardware that changes what’s algorithmically possible. Tens of PB/s of memory bandwidth and fine-grained dataflow execution open design spaces that don’t exist on GPU clusters. 
• You will work alongside researchers in computational science, computer architecture, and performance engineering. The synthesis across these fields is central to ATG’s approach. 
• Your research will influence silicon - ATG’s findings directly shape the design of future Cerebras chips and systems. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

We are seeking R&D Engineers to join Cerebras' Advanced Technology Group. You will design and implement workloads that establish new performance benchmarks on wafer-scale hardware, leveraging architectural features that no traditional platform offers. The 
scope ranges from large-scale scientific simulations to emerging AI/ML models, and the work sits at the intersection of algorithm design, compiler co-optimization, and hardware architecture. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories. 

What You Will Do 

• Design and implement challenging scientific computing and AI workloads on Cerebras’ Wafer-Scale Engine, targeting performance results that advance the state of the art. 
• Lead algorithm–hardware co-design efforts with internal R&D teams and external research partners, turning architectural capabilities into measurable application-level advantages. 
• Build analytical performance models that quantify bottlenecks, guide optimization, and inform future chip and compiler design decisions. 
• Contribute to Cerebras’ multi-year technology roadmap by identifying high-impact workloads, proposing architectural experiments, and validating them on silicon. 
• Publish findings and present at top-tier conferences and journals; represent Cerebras in the broader HPC and AI research communities. 

What We Are Looking For 

• PhD in Computer Science, Engineering, Applied Mathematics, Physics, or a related quantitative field preferred. Exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Deep experience in at least one of the following: computer architecture and accelerator design; parallel, distributed, or high-performance computing; numerical methods and scientific simulation; AI/ML theory and model design at a mathematical level. 
• Strong ability to analytically model and optimize the performance of complex systems and algorithms. 
• Track record of published research or patents in relevant venues. 
• Proficiency in C and Python; comfort working close to hardware. 
• Excellent communication and interpersonal skills: able to present complex technical material to both specialist and cross-functional audiences, and to collaborate effectively in a fast-paced, small-team environment. 

Areas Of Particular Interest 

We are hiring across several focus areas. Exceptional depth in one or more of the following is a strong signal: 

• Computational science: researchers who can bring insights from numerical methods and simulation into AI, or couple simulation and learning into joint computational workflows. Depth in hydrodynamics, solid mechanics, electromagnetics, molecular dynamics, or related PDE-based fields. 
• AI/ML foundations: deep understanding of model architecture, optimization methods, and their statistical underpinnings—the ability to design from first principles, not just apply established recipes. 
• Computer architecture: microarchitecture design, computing paradigms at the circuit and datapath level, memory hierarchy design. 
• Performance engineering: roofline modeling, bandwidth analysis, kernel optimization, communication-computation overlap, and compiler-level tuning for novel hardware. 

Why This Opportunity Is Exciting And Unique 

• Build on a fundamentally different architecture, unconstrained by GPU assumptions. 
• Publish and open-source your research. We present at Supercomputing, SIAM, IEEE, NeurIPS, and beyond. 
• Work on the fastest AI system in the world, with direct access to the hardware your compiler targets. 
• Join at a pivotal moment: Cerebras is pre-IPO with strong commercial traction and rapid growth. 
• Be part of a small, technical team with high autonomy, minimal bureaucracy, and a culture that values depth over hierarchy. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

About the group:

Branch is looking for a Principal Product Operations leader with a proven background building scalable processes and growing high-performing teams in a SaaS environment.

This newly created opportunity reports directly to the VP of Product and owns all product operations to drive operational excellence. The ideal candidate brings a demonstrated ability to work horizontally and vertically across the organization — bridging product, data, engineering, and customer-facing teams through strong cross-functional partnerships.

In this role, you will lead cross-functional initiatives and will be responsible for designing and optimizing the end-to-end product development lifecycle, leveraging AI-powered tools and workflow automation to accelerate delivery, eliminate process bottlenecks, and surface actionable insights from data. This includes integrating AI into how we synthesize customer feedback, track roadmap health, and enable teams to make faster, better-informed decisions.

This position sits at the intersection of operational efficiency, customer-centricity, and intelligent automation — ensuring our product teams are equipped to move with speed and precision in a rapidly evolving landscape.

Key Responsibilities

• Build and scale the Product Operations function, including establishing how AI tools augment each operational role and where automation can reduce manual coordination overhead.
• Define and execute the strategic vision for product operations, establishing frameworks that enable product-led growth and operational excellence at scale — with a deliberate roadmap for how AI adoption evolves across the product org over time.
• Own end-to-end product lifecycle operations including planning processes, prioritization frameworks, delivery mechanisms, and post-launch measurement systems .
• Identify, pilot, and operationalize AI-powered tools and agentic workflows across product, engineering, and design teams, evaluating where AI can handle execution, so teams focus on higher-order decision-making.
• Lead cross-functional initiatives spanning product, engineering, GTM, and customer success to accelerate time-to-market and improve feature adoption, using automated coordination and shared intelligence layers to reduce friction across team boundaries.
• Design and operationalize a Voice of the Customer program that integrates quantitative and qualitative signals, including in-app analytics, support data, user research, and revenue impact, and deploy AI to continuously synthesize that signal at scale into prioritized, actionable product insights.
• Partner with Product Leadership and the executive team on strategic planning, resource allocation, and portfolio management decisions.
• Own product knowledge management, ensuring internal teams and customers understand product capabilities and roadmap direction, including building AI-assisted tools for self-serve knowledge access and employee onboarding.
• Establish and report on operational health metrics including delivery predictability, cycle times, adoption rates, and team efficiency indicators, instrumenting dashboards and alerting systems that surface anomalies automatically and reduce reliance on manual reporting.
  
  

You’ll be a good fit if you have:

Required:

• 12+ years in product management, product operations, technical program management, or strategy roles, with 6+ years leading operations or cross-functional teams in a B2B SaaS environment.
• Deep domain expertise in B2B SaaS product operations, preferably in adtech, martech, developer tools, or infrastructure platforms, with an understanding of how AI is reshaping product development cycles and team operating models in these spaces.
• Demonstrated success implementing organization-wide process transformations and change management in companies with 300+ employees or high-growth environments. Experience driving adoption of AI-powered tooling and workflows at scale.
• Strong executive presence with the ability to act as a translator between technical and business stakeholders, influencing leadership decisions and driving alignment across competing priorities using clear, data-backed narratives.
• Hands-on proficiency with the modern product stack: analytics platforms (Amplitude, Mixpanel), collaboration and roadmapping tools (Linear, Jira, Productboard), experimentation frameworks, and data warehousing — plus working familiarity with AI and automation platforms (n8n, Zapier, Make, or comparable tooling).
• Practical AI fluency: experience deploying AI/ML workflows into product development processes, building or shipping products with AI capabilities, and a working understanding of core concepts (LLMs, agents, RAG, prompt engineering) sufficient to evaluate tools, guide implementation, and hold technical teams accountable.
• Proven track record of establishing metrics-driven cultures. Experience designing dashboards, goal frameworks, and operational reporting that surface actionable insights at the leadership level, with increasing emphasis on AI-assisted anomaly detection and automated reporting pipelines.
• Strategic systems thinker who can redesign workflows from a zero-based, outcome-first perspective rather than automating legacy processes. Focus on translating business objectives into operational frameworks while remaining hands-on when needed.
• Exceptional communication skills with the ability to distill complex operational challenges into clear narratives for technical and non-technical audiences.
• Experience leading in fast-paced, high-ambiguity environments with shifting business needs, with particular comfort managing the pace of change that comes with integrating rapidly evolving AI capabilities into existing team workflows and product processes.

This role is 100% remote in Canada. This role does not qualify for relocation or visa sponsorship. 

In accordance with applicable law, the following represents a reasonable estimated compensation range for this role: the estimated pay range for this role, if based in Canada is 175,000 CAD to 227,000 CAD. Please note that this information is provided for those hired in Canada only. Compensation for candidates outside of Canada will be based on the candidate’s specific work location. Actual compensation will be determined based on skills, experience, and geographic location and may be more or less than the amount shown above. This role additionally includes a 10% annual bonus tied to company goals. 

LayerZero

The Future is Omnichain.

Founded in 2021, LayerZero’s vision is to create a community of cross-chain developers, building dApps that are no longer constrained by individual blockchain capabilities. With LayerZero's simple, generic messaging protocol, builders will develop cross-chain dApps designed to unify the power of individual blockchains.

We are funded by the best investors in the world including:

a16z, Sequoia, PayPal, Binance Ventures, Coinbase Ventures, Uniswap Labs, Circle Ventures, Delphi

ABOUT THE ROLE

We’re looking for a technical Product Manager with a computer science background, hands-on software engineering experience, and a track record of building and shipping developer-focused software products. You will act as the connective tissue across engineering, design, and external partners; owning the problem space, driving clarity, and pushing execution from 0→1 and beyond.

WHAT YOU’LL DO

• Own end-to-end product development for core LayerZero infrastructure and API surfaces - vision, roadmap, requirements, and execution.
• Partner closely with engineers; understand technical constraints, read code-level designs, and actively participate in architectural discussions.
• Drive alignment across teams by overcommunicating vision, use cases, and decisions - tailoring communication to technical and non-technical audiences.
• Maintain relentless clarity on user needs by continually engaging with developers, partners, and integrators; synthesize qualitative and quantitative insights.
• Break down ambiguous problems, validate assumptions, and prevent premature solutioning; ensure the team is solving the right problems.
• Advocate for design quality and usability, even for deeply technical workflows; sweat the details.
• Influence cross-functional stakeholders through trust, execution, and strong product judgment, not authority.
• Unblock engineering, drive momentum, and take ownership for outcomes end-to-end.

ABOUT YOU

• You have a computer science degree or equivalent technical background.
• You have 2–5+ years of software engineering experience and can comfortably lead technical discussions.
• You have 3–6+ years of product management experience, ideally owning API, developer, or infrastructure products.
• You think like an owner; you drive work forward even without authority or perfect information.
• You communicate clearly, proactively, and repeatedly to ensure alignment. You are able to effectively tailor your communication to different types of stakeholders.
• You are comfortable in fast-moving, low-process environments and thrive in ambiguity.
• You care deeply about quality, user experience, and execution.
• Ideally, you have experience in Web3, distributed systems, or developer-focused platforms, but it’s not required.

Equal Opportunity Employer

LayerZero Labs is committed to fostering a diverse and inclusive workplace. LayerZero Labs is an equal opportunity employer and does not discriminate on the basis of race, national origin, religion, gender, gender identity, sexual orientation, marital status, protected veteran status, disability, age, or any other legally protected status.