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Executive Quantitative Analyst Google Jobs (NOW HIRING)

Octus

Quantitative Analyst

$135K - $150K/yr

The Quantitative Analyst will work together with the analytics team, data team, and business ... Experience with AI tools, such as Claude Code or Google Gemini At Octus, we consider a range of ...

AdHarmonics

Quantitative Analyst

Cambridge, MA

Quantitative Analyst The role, quantitative analyst, is ideal for someone who enjoys finding trends ... the Google auction, and expanding our onsite lead routing rules based on analysis of consumer ...

Adharmonics

Quantitative Analyst

Cambridge, MA · On-site

Quantitative Analyst The role, quantitative analyst, is ideal for someone who enjoys finding trends ... the Google auction, and expanding our onsite lead routing rules based on analysis of consumer ...

Octus

Quantitative Analyst

$135K - $150K/yr

Role We are seeking a Quantitative Analyst for the analytics team at Sky Road, Octus ... Experience with AI tools, such as Claude Code or Google Gemini At Octus, we consider a range of ...

Ventus Solutions

Quantitative Analyst SETA

Arlington, VA · On-site

$150 - $195/hr

Ventus Executive Solutions is a dynamic small business at the forefront of innovation and ... Ventus Executive Solutions is seeking a skilled Quantitative Analyst SETA to support an innovative ...

Ventus Solutions

$150 - $195/hr

Ventus Executive Solutions is a dynamic small business at the forefront of innovation and ... Ventus Executive Solutions is seeking a skilled Quantitative Analyst SETA to support an innovative ...

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Executive Quantitative Analyst Google information

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$56.5K

$133.9K

$240K

How much do executive quantitative analyst google jobs pay per year?

As of Aug 27, 2026, the average yearly pay for executive quantitative analyst google in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What is the difference between Executive Quantitative Analyst Google vs Quantitative Analyst?

AspectExecutive Quantitative AnalystQuantitative Analyst
CredentialsAdvanced degrees (Master's/PhD), certifications like CFA or CQFBachelor's or Master's in finance, mathematics, or related fields
Work EnvironmentHigh-level strategic roles, often in leadership teams, focused on complex modelingData analysis, model development, and support for trading or investment decisions
Employer & IndustryLarge tech firms, hedge funds, investment banksFinancial institutions, asset management firms, tech companies

Executive Quantitative Analysts Google typically hold senior credentials and focus on strategic, high-impact modeling, while Quantitative Analysts perform core data analysis and model development. Both roles are vital in finance and tech sectors but differ in scope and seniority.

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Executive Quantitative Analyst Google jobs near you
Infographic showing various Executive Quantitative Analyst Google job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $133,877 per year, or $64.4 per hour.

Quantitative Analyst

Wright-Patt Credit Union Inc.

Beavercreek, OH • On-site

$90 - $130/hr

Other

Re-posted 5 days ago

Wright-Patt Credit Union rating

5.8

Company rating: 5.8 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

Job description

The Quantitative Analyst is responsible for leading high-impact statistical analysis, measurement design, and scalable analytics solutions that improve business performance and decision-making. This role partners closely with Strategy, Product, and Technology teams to evaluate key initiatives, identify performance drivers, develop statistically sound measurement approaches, and deliver executive-ready insights that influence priorities and investments. The Quantitative Analyst combines strong analytical depth with automation and repeatability, ensuring insights are accurate, timely, and operationally useful.

1) High-Impact Quantitative Analysis & Decision Science (30%)
  • Perform exploratory data analysis, segmentation, and trend analysis to uncover patterns and anomalies.
  • Apply statistical techniques such as hypothesis testing, confidence intervals, correlation, and regression analysis.
  • Identify opportunities for growth, efficiency, and experience improvement using data-backed recommendations.
  • Deliver decision-ready outputs that connect analysis to actions, tradeoffs, and expected outcomes.
2) Experimentation, Testing, and Impact Evaluation (25%)
  • Support A/B testing and experiment analysis including test design inputs, lift measurement, and interpretation.
  • Partner with product and business teams to define success metrics, baselines, and measurement plans.
  • Evaluate initiative effectiveness using controlled comparisons, pre/post analysis, and statistical significance testing.
  • Develop standardized experiment readouts and decision frameworks to improve speed and consistency.
3) Predictive Analytics & Optimization (20%)
  • Partner with data scientists to support model development by preparing datasets, validating features, and interpreting outputs.
  • Build and maintain scoring frameworks (propensity, prioritization, classification support) aligned to business use cases.
  • Support model evaluation using practical performance measures (lift, precision/recall, error rates).
  • Translate model outputs into actionable recommendations and operational workflows.
4) Automation & Scalable Analytics Delivery (15%)
  • Develop automated analysis workflows using SQL and Python to reduce manual effort.
  • Build reusable scripts, templates, and standardized datasets to improve reliability and consistency.
  • Partner with data engineering teams to improve data availability and support repeatable pipelines.
  • Implement monitoring and alerting for key performance indicators and threshold-based changes.
5) Communication, Visualization, and Executive Enablement (10%)
  • Build clear, executive-ready summaries and visualizations tied to business outcomes.
  • Present findings and recommendations to senior leaders and cross-functional teams.
  • Communicate confidence levels, limitations, and tradeoffs in a practical way.
  • Ensures proper policies, procedures, risk mitigation activities, and operating controls are followed. Reports gaps in policies, procedures, and operating controls to leadership to ensure member impact and risk is mitigated.
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