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Executive Decision Scientist Jobs (NOW HIRING)

Globenet Consulting Corp

Decision Scientist

Lynnwood, WA · On-site

$50 - $55/hr

Create executive-ready presentations covering performance, risks, opportunities, and recommended ... Promote best practices in decision science, experimentation, product analytics, and AI-enabled ...

New

Judge Group, Inc.

Data Scientist IV

Bridgewater, NJ · On-site

Job Title: Technical Process Manager - Decision Scientist cum Consultant/ Data Scientist Iv ... executive decision-making and create business impact. Key Responsibilities: 1. Product Mindset ...

Judge Group, Inc.

Data Scientist IV

Bridgewater, NJ · On-site

Data Scientist Iv Location- Basking Ridge, NJ (Hybrid) 8 days/month in office (typically 2 days a ... executive decision-making and create business impact. Key Responsibilities: 1. Product Mindset o ...

Instacart

Senior Marketing Decision Scientist II

OR · Remote

As a Senior Marketing Decision Scientist II, you will shape how we measure, forecast, and optimize ... Create executive-ready dashboards and narratives in tools like Looker or Mode that track KPIs ...

Instacart

Senior Marketing Decision Scientist II

As a Senior Marketing Decision Scientist II, you will shape how we measure, forecast, and optimize ... Create executive-ready dashboards and narratives in tools like Looker or Mode that track KPIs ...

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Executive Decision Scientist information

What are the key skills and qualifications needed to thrive as an Executive Decision Scientist, and why are they important?

To thrive as an Executive Decision Scientist, you need strong expertise in data analytics, statistical modeling, and business strategy, typically supported by an advanced degree in a quantitative field. Proficiency with tools such as Python, R, SQL, and data visualization platforms like Tableau, as well as experience with machine learning frameworks, is essential. Outstanding communication, critical thinking, and stakeholder management set top performers apart in this role. These skills are crucial for translating complex data insights into strategic business recommendations that drive executive decision-making.

What is a decision scientist's salary?

The average salary for a decision scientist typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Senior decision scientists or those with specialized skills in data analysis and machine learning can earn higher salaries, often exceeding $150,000. Compensation may also include bonuses and benefits related to data-driven roles.

Is 40 too late for data science?

For an Executive Decision Scientist or similar data science roles, starting a career at 40 is not too late. Many professionals transition into data science later in life, leveraging prior experience, and can succeed by developing relevant skills such as programming, statistics, and machine learning through online courses or certifications.

What are Executive Decision Scientists?

Executive Decision Scientists are professionals who use data analytics, quantitative modeling, and business strategy to support high-level decision-making within organizations. They combine expertise in data science, statistics, and business acumen to inform and guide executives on complex business challenges. Their work often involves analyzing large datasets, developing predictive models, and translating insights into actionable strategies that align with organizational goals. Executive Decision Scientists play a key role in driving data-driven transformation and ensuring that leadership decisions are supported by robust evidence.

How much do decision scientists make?

Decision scientists typically earn a median salary ranging from $80,000 to $130,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in data analysis, machine learning, and programming can earn higher salaries, often exceeding $150,000.

How do Executive Decision Scientists typically collaborate with senior leadership to influence business strategy?

Executive Decision Scientists frequently work closely with senior executives, providing data-driven insights and recommendations that shape high-level business decisions. They translate complex analytical findings into actionable strategies, ensuring that leadership understands both the opportunities and risks. This role often involves regular presentations, cross-functional workshops, and advising on strategic initiatives, requiring strong communication skills and the ability to connect technical analysis with business objectives. Successful Executive Decision Scientists build trust by aligning their work with organizational goals and actively participating in strategic planning sessions.

What is the difference between Executive Decision Scientist vs Data Analyst?

AspectExecutive Decision ScientistData Analyst
Required CredentialsAdvanced degrees in data science, statistics, or related fields; experience with machine learningBachelor's or master's in data analysis, statistics, or related fields
Work EnvironmentStrategic, high-level decision-making teams; executive meetingsOperational teams; reporting and data visualization tasks
Employer & Industry UsageCorporate, finance, tech firms focusing on strategic insightsVarious industries; operational data analysis
Search & Comparison IntentUnderstanding strategic roles and qualificationsOperational data analysis and reporting

Executive Decision Scientists focus on high-level strategic insights and predictive modeling to inform executive decisions, often requiring advanced degrees and experience. Data Analysts handle operational data, generate reports, and support daily business functions. While both roles analyze data, the Executive Decision Scientist operates at a strategic level, whereas Data Analysts focus on tactical, operational tasks.

Which 3 jobs will survive AI?

For an Executive Decision Scientist, roles that require complex strategic thinking, creativity, and nuanced judgment are less likely to be fully automated by AI. These include executive leadership positions, high-level strategic planning, and roles involving ethical decision-making. Skills such as advanced data analysis, critical thinking, and domain expertise will remain valuable in adapting to AI-driven changes.
What cities are hiring for Executive Decision Scientist jobs? Cities with the most Executive Decision Scientist job openings:
What are the most commonly searched types of Decision Scientist jobs? The most popular types of Decision Scientist jobs are:
What states have the most Executive Decision Scientist jobs? States with the most job openings for Executive Decision Scientist jobs include:
Executive Decision Scientist jobs near you

Decision Scientist

Globenet Consulting Corp

Lynnwood, WA • On-site

$50 - $55/hr

Full-time

Posted yesterday

New

Job description

Benefits:
  • Competitive salary
  • Opportunity for advancement
  • Training & development

Decision ScientistAbout the Role
The Decision Scientist will partner with Digital Product Managers, Engineering, UX, Operations, and Analytics teams to drive data-informed decisions across digital ordering experiences.
This role combines advanced analytics, experimentation, forecasting, AI-enabled insights, and business performance analysis to improve digital experiences, operational efficiency, and product outcomes. The ideal candidate brings strong analytical expertise, business acumen, and the ability to translate complex findings into clear recommendations for product leaders and senior executives.
Benefits and Opportunities
  • Influence product strategy, roadmap priorities, and investment decisions
  • Work with large-scale data across cloud and on-premises environments
  • Build AI-enabled analytics tools and self-service reporting capabilities
  • Lead experimentation, forecasting, and product measurement initiatives
  • Collaborate with cross-functional product, engineering, UX, and operations teams
Core Responsibilities
Product Analytics and Decision Support
  • Analyze product, operational, transaction, and digital experience performance to identify trends, risks, root causes, and opportunities.
  • Develop recommendations that influence product prioritization, roadmap planning, feature optimization, and investment decisions.
  • Build analytical models, forecasts, scenario-planning tools, and opportunity-sizing assessments.
  • Define key performance indicators and monitor product, operational, and business outcomes.
  • Quantify business impact and measure return on investment for product initiatives.
Experimentation and Product Measurement
  • Define measurement strategies and success criteria for new products, features, and digital experiences.
  • Design and evaluate A/B tests, pilots, and experiments.
  • Measure adoption, engagement, conversion, transaction success, operational efficiency, and feature utilization.
  • Create standardized product measurement frameworks across platforms and channels.
  • Evaluate pilot results and provide recommendations for broader implementation.
Dashboards, Data Products, and AI Enablement
  • Build and maintain product health scorecards, performance dashboards, and automated reporting solutions.
  • Develop AI-enabled and self-service analytics tools for product teams.
  • Automate recurring analysis, monitoring, and reporting activities.
  • Partner with data engineering and analytics teams to improve data quality, accessibility, and reporting capabilities.
  • Enhance existing dashboards and data products based on evolving business needs.
Business Problem-Solving and Communication
  • Lead analysis of complex and ambiguous business questions.
  • Develop hypotheses, research approaches, measurement plans, and actionable recommendations.
  • Translate technical analysis into clear business implications.
  • Create executive-ready presentations covering performance, risks, opportunities, and recommended actions.
  • Present findings to product leadership and senior executives.
  • Promote best practices in decision science, experimentation, product analytics, and AI-enabled reporting.
Required Qualifications
  • Bachelor’s degree in analytics, data science, statistics, economics, business, computer science, or a related field preferred.
  • At least four years of experience in strategic analytics, product analytics, or decision support.
  • At least five years of experience communicating analytical findings and producing detail-oriented deliverables.
  • Advanced proficiency in SQL, Excel, Python, R, SAS, Tableau, or Power BI.
  • Experience with Azure Data Lake Storage, Azure SQL Server, Oracle, AWS, on-premises systems, and web-based data sources.
  • Experience performing exploratory data analysis, data cleansing, transformation, aggregation, and large-scale data manipulation.
  • Knowledge of experimental design, A/B testing, forecasting, and scenario planning.
  • Ability to explain complex technical findings to non-technical audiences.
  • Strong business acumen and understanding of operational and digital product processes.
Technology
  • Azure
  • Oracle
  • SQL Server
  • Python, R, and SAS
  • Tableau or Power BI
  • Microsoft Office Suite
  • Smartsheet
Preferred: Experience with Databricks.
Key Success Measures
Success may be measured through digital experience performance, order-entry speed, error rates, adoption, engagement, cart completion, checkout success, payment speed, transaction reliability, order accuracy, throughput, peak-hour performance, feature utilization, and satisfaction indicators.
Ready to make an impact? Apply now and join us on our journey!