The Director, US Forecasting & Analytics – Vaccines & Immune Therapies is a senior commercial insights leader responsible for US demand forecasting and analytics across the V&I portfolio. The role is predominantly forecast-focused, serving as the US forecasting lead and strategic thought partner to Marketing, Finance, Market Access, and US teams.

Responsibilities:

US Forecasting Leadership (Core Accountability)

• Lead US short-term and long-term demand forecasts (TRx, NBRx, volume, patients, revenue) for V&I assets using robust, patient-based and market-based models
• Own forecast methodology, assumptions, and governance, ensuring objectivity, transparency, and consistency with enterprise standards
• Integrate primary market research, epidemiology, competitive intelligence, access dynamics, and real-world data into forecast models
• Proactively identify and quantify key risks and opportunities through scenario and sensitivity analyses
• Partner closely with Finance, Market Access & Pricing, Marketing, Sales, Medical, and Global Forecasting to ensure alignment on assumptions and implications
• Support business planning, governance reviews, and opportunity assessments with clear, executive-ready narratives
• Serve as a trusted advisor to senior marketing and finance leadership, clearly articulating forecast drivers and changes

Analytics & Resource Leadership (Enablement)

• Provide leadership over forecasting-adjacent analytics, ensuring advanced analytics and insights are embedded into forecasting and business planning
• Manage and prioritize internal analysts, contractors, and external vendors supporting forecasting and analytics deliverables
• Partner with data analytics resources, Global IA&F, and GIBEX capability teams to deploy new tools, data sources, and modeling approaches
• Champion and identify new ways to embed AI and advanced automation into the practice of data analytics and forecasting to drive efficiency, scalability, and decision quality
• Champion continuous improvement in forecasting processes, AI-enabled modeling, and automation
• Contribute to the development and sharing of best practices across the V&I forecasting community

Essential for the role

• Bachelor’s degree in a quantitative, scientific, or business-related field required (e.g., Statistics, Economics, Mathematics, Engineering, Computer/Data Science).
• 8+ years’ experience in US pharmaceutical commercial forecasting, including in-market and late-stage pipeline assets
• Hands-on model ownership experience (build, refresh, and performance tracking) across short- and long-term horizons
• Expertise in scenario-based forecasting, sensitivity analysis, and driver-based narratives to support senior decision-making
• Strong capability integrating multiple data types (e.g., IQVIA, claims, epidemiology, RWD/RWE, primary research) into coherent, decision-grade forecasts
• Working knowledge of advanced analytics/ML approaches (e.g., time series, causal inference, ensembles) and where they add value vs. traditional methods
• Fluency in modern analytics tooling and automation (e.g., Python/R/SQL, BI/visualization), with ability to partner effectively with data engineering and analytics teams
• Demonstrated forecast governance and model risk discipline (traceable assumptions, documentation, and clear explanations)
• Strong understanding of US market access and payer dynamics and how they impact demand (coverage, contracting, channel, policy)
• Exceptional communication: translates complex analysis into clear, executive-ready insights, options, and recommendations
• Strong commercial competence across key demand levers (positioning, adoption, competitive dynamics, lifecycle events)

Desirable for the role

• Advanced degree preferred (e.g., MBA, MS, PhD in Statistics, Economics, Decision Sciences, Data Science, or related discipline).
• Vaccines and/or Rare Disease experience, including familiarity with immunization dynamics, patient-based forecasting, and lifecycle management in preventive or immune-mediated therapies
• Change leadership: builds adoption for new tools, processes, and ways of working across cross-functional stakeholders
• Product mindset for forecasting: defines user needs, success metrics, and a roadmap for portfolio forecasting capabilities
• Model lifecycle practices (e.g., reproducibility, versioning, monitoring/drift awareness); familiarity with MLOps concepts

Office Working Requirements

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

#LI-Hybrid

Date Posted 10-Apr-2026 Closing Date 23-Apr-2026 Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

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You will partner closely with Product Management, Engineering, Design, and Go-to-Market teams to drive programs from concept through launch, ensuring high-quality delivery, predictable execution, and strong adoption.

This role balances strategic influence with hands-on execution,translating product strategy into clear delivery plans, managing dependencies and risks, and ensuring launches deliver measurable customer and business impact.

Responsibilities:

• Lead execution of customer-facing features such as Models, Weave, and other emerging products
• Partner closely with Product Management, Engineering, Design, and Go-to-Market teams to drive programs from concept through launch
• Ensure high-quality delivery, predictable execution, and strong adoption
• Balance strategic influence with hands-on execution

Requirements:

• Bachelor’s degree in a technical field or equivalent practical experience
• 7+ years of experience managing large-scale, complex programs in SaaS, Cloud, or ML/AI environments
• Demonstrated experience delivering customer-facing product features and launches end-to-end
• Proven ability to lead cross-functional programs involving Product, Engineering, Design, and Go-to-Market teams

Preferred:

• Master’s degree or advanced technical degree
• Familiarity with ML developer workflows, model lifecycle management, or AI tooling
• Experience influencing product and technical direction to align with long-term platform strategy

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

What We Offer

The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance - 100% paid for by CoreWeave
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

Our Workplace

While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

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On this team, you will build and operate the ML infrastructure and product services that enable trust and intelligence across Plaid's network. You'll own feature engineering, offline training and batch scoring, online feature serving, and real-time inference so model outputs directly power partner-facing fraud & trust products and bank intelligence features.

Responsibilities

• Embed model inference into Network Enablement product flows and decision logic (APIs, feature flags, backend flows).
• Define and instrument product + ML success metrics (fraud reduction, retention lift, false positives, downstream impact).
• Design and run experiments and rollout plans (backtesting, shadow scoring, A/B tests, feature-flagged releases) to validate product hypotheses.
• Build and operate offline training pipelines and production batch scoring for bank intelligence products.
• Ship and maintain online feature serving and low-latency model inference endpoints for real-time partner/bank scoring.
• Implement model CI/CD, model/version registry, and safe rollout/rollback strategies.
• Monitor model/data health: drift/regression detection, model-quality dashboards, alerts, and SLOs targeted to partner product needs.
• Ensure offline and online parity, data lineage, and automated validation / data contracts to reduce regressions.
• Optimize inference performance and cost for real-time scoring (batching, caching, runtime selection).
• Ensure fairness, explainability and PII-aware handling for partner-facing ML features; maintain auditability for compliance.
• Partner with platform and cross-functional teams to scale the ML/data foundation (graph features, sequence embeddings, unified pipelines).
• Mentor engineers and document team standards for ML productization and operations.

Qualifications

• Must-haves:
• Strong software engineering skills including systems design, APIs, and building reliable backend services (Go or Python preferred).
• Production experience with batch and streaming data pipelines and orchestration tools such as Airflow or Spark.
• Experience building or operating real-time scoring and online feature-serving systems, including feature stores and low-latency model inference.
• Experience integrating model outputs into product flows (APIs, feature flags) and measuring impact through experiments and product metrics.
• Experience with model lifecycle and operations: model registries, CI/CD for models, reproducible training, offline & online parity, monitoring and incident response.
• Nice to have:
• Experience in fraud, risk, or marketing intelligence domains.
• Experience with feature-store products (Tecton / Chronon / Feast / internal) and unified pipelines.
• Experience with graph frameworks, graph feature engineering, or sequence embeddings.
• Experience optimizing inference at scale (Triton/ONNX/quantization, batching, caching).

Additional Information

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable.

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Forge turns cutting-edge research into enterprise-ready capabilities by powering model fine-tuning, reinforcement learning and post-training workflows. By working at the intersection of research and product it provides customers with the tools to train specialized models that deliver real-world business value.

As the PM leading Forge you will shape a 0-1 product with significant business impact and the potential to grow offering while defining how organizations train and deploy the next generation of AI models.

Key Responsibilities:

Define the Future • Set the vision: Shape and evangelize a compelling product strategy for Forge ensuring alignment with company goals and market opportunities.

Spot the gaps: Lead market and UX research to uncover unmet needs, competitive whitespaces, and emerging trends in SOTA AI post-training capabilities.

Build & Ship • Own the lifecycle: Drive end-to-end product development, from ideation to launch and iteration,balancing speed, quality, and user delight.

Champion the user: Partner with design and research to craft intuitive, high-impact experiences, using data and feedback to refine continuously.

Scale, Execute, & Enable • Go-to-market: Collaborate with marketing and sales to launch products successfully, including pricing, positioning, and adoption strategies.

Align stakeholders: Rally engineering, design, and business teams around priorities, trade-offs, and timelines.

Prioritize ruthlessly: Maintain a dynamic roadmap that delivers quick wins while advancing long-term bets.

Requirements:

Product Management Experience 5+ years of relevant experience in new, competitive, fast-paced and ambiguous environments with a track record of building and scaling complex AI/ML or infrastructure solutions.

Technical skills - Very good understanding of training pipelines, RL loops, and model deployment architectures,

Expertise in AI model lifecycle management, including fine-tuning, evaluation, and serving.

Experience with Infrastructure as Code (IaC), containerization, and scalable deployment modes (e.g., on-prem, VPC, cloud).

Familiarity with Kubernetes/Slurm is a strong plus.

User obsession Relentless focus on solving real user problems, backed by data and qualitative insights.

Cross-functional influence Proven ability to align and inspire engineering, design, and go-to-market teams without direct authority.

Problem-solving Balance big-picture thinking with hands-on problem-solving , you’re equally comfortable crafting a roadmap, diving into metrics and running technical tests.

Communication: Crisp, persuasive storytelling for executives, teams, and users , ability to distill complex technical concepts (e.g., RL, LoRA, SFT) into clear narratives for docs, decks, and workshops.

Adaptability: Thrive in high-velocity, dynamic settings where priorities shift quickly.

Collaboration: Low ego + high EQ , you build trust and drive decisions through clarity, not hierarchy.

Autonomy: Self-directed with a bias for action, you own outcomes end-to-end.

Preferred Qualifications:

Infrastructure knowledge - Strong knowledge of model training, model architectures, etc.

Strong understanding how complex architectures are designed and impact of deployment modes

Proficient coding skills are strongly recommended

Kubernetes know-how strongly recommended

Growth mindset: Deep familiarity with product-led growth strategies (e.g., viral loops, onboarding optimization, monetization, etc.).

Builder’s mindset: Founder or early-stage PM experience , you’ve turned 0 → 1 ideas into products users love.

Technical depth: Ability to prototype, hack, or dive into code when needed.

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