Skills this job asks for
BudgetingStatisticsLeadershipMachine learning
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 46 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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✓
What Klaviyo INC paid sponsored hires in similar roles3 certified filings for “Deliverability Operations Analyst” (Data Scientists) in MA: $114k–$142k, median $116k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 46 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Klaviyo INC paid sponsored hires in similar roles
- 3 certified filings for “Deliverability Operations Analyst” (Data Scientists) in MA: $114k–$142k, median $116k. Most were filed at wage level II (100%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
Lead Product Data Scientist, Forecasting
About the Team
Klaviyo's Product Data Science team plays a critical role in shaping how we understand, measure, and improve business performance. We partner closely with Product, Engineering, Finance, and Go-to-Market teams to turn complex data into actionable insights that inform product strategy, financial planning, and long-term growth.
As Klaviyo continues to scale its platform, expand its product portfolio, and introduce new AI-powered capabilities, the ability to accurately forecast business outcomes and understand the drivers behind them has never been more important.
Our team combines rigorous statistical modeling, advanced analytics, and deep business understanding to help leaders make better decisions. We believe data science should be embedded in the product development lifecycle, influencing strategic investments, identifying opportunities, and enabling teams to move quickly and confidently.
About the Role
We're looking for a Lead Product Data Scientist, Forecasting to own and advance Klaviyo's forecasting capabilities, combining deep technical expertise with strong business judgment to influence some of our most important product and strategic decisions.
This is a highly visible, hands-on technical leadership role at the intersection of data science, product strategy, and business performance. You'll lead the development of sophisticated revenue forecasting models, establish rigorous evaluation standards, and help the organization better understand how customer behavior, product investments, pricing decisions, and market dynamics influence business outcomes.
This isn't just about building accurate models or reporting on historical trends. We're looking for someone who can connect advanced statistical methods to real business questions, challenge assumptions, investigate unexpected outcomes, and translate complex findings into clear recommendations that shape decisions.
You'll work closely with Product, Finance, Engineering, and Go-to-Market leadership to build scalable forecasting systems and self-service analytical capabilities. You'll also help define the technical direction of forecasting at Klaviyo, mentor other data scientists, and establish the methodologies and standards that make forecasting a trusted, repeatable practice across the company.
How You'll Make a Difference
• Own revenue forecasting end to end , from problem framing and data preparation through model development, evaluation, deployment, and ongoing monitoring, ensuring forecasts serve as trusted inputs to business planning and product decisions.
• Build sophisticated forecasting models across multiple time horizons and levels of granularity, leveraging hierarchical forecasting, probabilistic and Bayesian methods, classical time series techniques, machine learning, and emerging time series foundation models.
• Establish forecasting standards and governance by defining how the organization measures accuracy, bias, calibration, and uncertainty, creating consistent and rigorous approaches to model evaluation and performance.
• Lead the technical direction of forecasting , evaluating modeling approaches, reviewing technical designs, mentoring other data scientists, and raising th
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