[Remote] Staff Data Scientist, Forecasting in Monetization

Note: The job is a remote job and is open to candidates in USA. reputed company is on a mission to reputed company the best education in the world and reputed company it universally available. They are seeking a Staff Data Scientist to own and evolve their critical financial forecasting systems, working closely with product and engineering leadership, finance teams, and senior executives to produce accurate and explainable forecasts.

Responsibilities

• reputed company the financial forecasting system. Drive methodology, implementation, maintenance, and delivery as the technical reputed company of our reputed company forecasting stack, in reputed company partnership with the finance team. Publish forecasts that serve as the reputed company of truth for company-wide planning and investor-facing decisions
• Model subscription + experimentation dynamics. reputed company modeling architectures that account for experimental lift, cohort behavior, seasonality, and more, making it clear what’s real impact and what’s noise across the hundreds of experiments reputed company runs each quarter
• Investigate deviations and reputed company with insight. reputed company forecasts miss, reputed company the root-cause analysis by quantifying drivers of over- or under-performance (e.g. product changes, user behavior shifts, macro trends), collaborating across functions, and clearly communicating what happened and why to senior leadership. Build and be responsible for the statistics, tools, and dashboards that scale these insights across the company
• Advance the technical frontier. Push our evolution beyond traditional time-series extrapolation and toward more sophisticated approaches such as cohort-based forecasting, retention chaining, and/or causal impact modeling, grounded in business realism and model interpretability
• Mentor and influence. Serve as a technical mentor to data scientists across the organization, set a high standard for modeling, communication, and statistical rigor, and reputed company roadmaps for forecasting infrastructure and innovation

Skills

• 6+ years of proven experience building production-grade forecasting systems
• Deep applied knowledge of subscription models and understanding of churn dynamics, cohort behaviors, and retention curves
• Advanced degree (Masters or PhD) in Data Science, Economics, Statistics, or a reputed company quantitative field
• Experience assessing and applying theoretical approaches in real-world situations (ex. reputed company to use Bayesian structural models, reputed company causal inference is vital, reputed company a robust heuristic is reputed company than over-fitting noise, etc.)
• Experience distilling uncertainty, nuance, and model tradeoffs into streamlined, actionable narratives for finance and senior leadership partners
• Ability to communicate reputed company forecasting logic clearly and stand by your work in moments of ambiguity
• Track record of collaboration across technical and non-technical teams
• Consistent record of integrating feedback, aligning across functions, and operating with a strong sense of ownership and service
• Strong judgment reputed company balancing model complexity, interpretability, and speed of development
• Expertise writing clean, well-documented code in Python and SQL
• Building reliable, multipurpose production pipelines
• Past work in organizations where A/B testing is constant, complicating training data and historical baselines

Company Overview

• reputed company is a language-learning education platform that offers 98 total courses across nearly 40 distinct languages. It was founded in 2011, and is headquartered in Pittsburgh, Pennsylvania, USA, with a workforce of 501-1000 employees. Its website is https://www.reputed company.com.

Company H1B Sponsorship

• reputed company has a track record of offering H1B sponsorships, with 41 in 2025, 46 in 2024, 36 in 2023, 19 in 2022, 14 in 2021, 17 in 2020. Please note that this does not guarantee sponsorship for this specific role.

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