Lead Decision Scientist (Web)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Decision Scientist (Web) based in United States.

This role offers the opportunity to shape critical business decisions through advanced analytics, experimentation, and data-driven strategy. You will partner closely with product, marketing, engineering, and finance teams to uncover insights that influence roadmaps, investments, and growth initiatives. The position focuses on transforming complex data into clear recommendations that improve digital experiences and business outcomes. You will lead analytics strategy for web products, leveraging statistical methods, causal inference, and experimentation frameworks. As part of an AI-native organization, you will help redefine how analytics teams use automation and AI tools to increase impact. This is a high-visibility role for a strategic thinker who enjoys solving ambiguous problems and turning insights into measurable action.

Accountabilities: In this role, you will act as a strategic analytics partner, owning the decision-making framework for web experiences and helping cross-functional teams understand customer behavior, optimize performance, and identify growth opportunities.

Partner with product, marketing, engineering, and finance teams to define analytics strategies, prioritize opportunities, and influence business decisions through data.

Build and communicate analytical narratives that transform complex findings into clear recommendations and actionable strategies for leadership and operational teams.

Analyze the complete digital customer journey, identifying conversion opportunities, user behavior trends, funnel improvements, and areas for optimization.

Design and evaluate experiments, including A/B testing and multivariate testing, using statistical methods and causal inference techniques to measure impact.

Develop measurement frameworks and key performance indicators that align user behavior insights with business objectives.

Collaborate with engineering teams to improve event tracking, data pipelines, and analytics infrastructure supporting digital performance measurement.

Integrate data from platforms such as Google Analytics, BigQuery, and Databricks to support reporting, experimentation, and decision-making.

Develop scalable self-service analytics solutions and reporting frameworks using industry best practices.

Use AI-powered tools and automation workflows to accelerate analysis, improve productivity, and help shape modern analytics practices.

Investigate consumer behavior across segments and markets to uncover trends that inform product, marketing, and revenue strategies.

Requirements

The ideal candidate combines strong analytical expertise, business judgment, and the ability to influence teams through data-driven insights. You should be comfortable working in ambiguous environments, asking the right questions, and connecting technical analysis with strategic outcomes.

6+ years of experience in analytics, data science, decision science, or a related field within a consumer-focused technology environment.

Bachelor’s degree or higher in a quantitative discipline such as economics, statistics, mathematics, operations research, or equivalent practical experience.

Strong experience applying causal inference methodologies, including techniques such as difference-in-differences, regression analysis, propensity score matching, or similar approaches.

Proven ability to influence product and business strategy through data analysis and measurable recommendations.

Advanced proficiency in SQL and Python or R for statistical analysis and data exploration.

Hands-on experience with experimentation platforms and optimization programs.

Strong knowledge of web analytics platforms such as Google Analytics 4 (GA4) and/or Adobe Analytics.

Experience collaborating with data engineering teams to build and maintain event tracking and centralized data environments.

Ability to communicate complex analytical concepts clearly to technical and non-technical stakeholders.

Experience using AI-assisted development and analytics tools to improve workflows and increase productivity.

Strong problem-solving mindset, ownership mentality, curiosity, and ability to independently identify opportunities.

Experience with subscription, e-commerce, or freemium business models is a plus.

Familiarity with tools such as Google Tag Manager, Tealium, dbt, revenue forecasting frameworks, LTV modeling, incrementality testing, or marketing mix modeling is preferred.

Benefits

Competitive compensation package:

United States: $133,000 - $195,000 USD base salary range.

Canada: $147,500 - $173,000 CAD base salary range.

Equity opportunities as part of the overall compensation package.

Comprehensive medical, dental, vision, life, and disability insurance plans.

Employer-supported retirement programs, including 401(k) matching in the US and RRSP/DPSP options in Canada.

Flexible paid time off and company-wide scheduled days off throughout the year.

Winter and summer company shutdown periods to support work-life balance.

Employee Assistance Program focused on mental wellness and personal support.

Learning and development programs to support career growth.

Remote work support, including equipment, tools, and reimbursement resources.

Remote-first working environment with flexibility across eligible locations.

Access to premium membership benefits and company products.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1