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Executive Data Science Jobs (NOW HIRING)

Walmart

Senior Manager, Data Science

Hayward, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning ... Establish success metrics, quantify business impact, and communicate results to executive ...

Five9

Vice President, Data Science

San Ramon, CA · On-site

The data science team is very much applied - their work directly makes its way into real products ... Internally, you will be expected to meet with product managers, executives and estaff, and be able ...

Five9

Vice President, Data Science

The data science team is very much applied - their work directly makes its way into real products ... Internally, you will be expected to meet with product managers, executives and estaff, and be able ...

Walmart

Senior Manager, Data Science

Milpitas, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning ... Establish success metrics, quantify business impact, and communicate results to executive ...

Five9

OR

As Vice President of Data Science, you will lead and grow our in-house data science team. This team ... Internally, you will be expected to meet with product managers, executives and estaff, and be able ...

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Executive Data Science information

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$26.5K

$93.6K

$184K

How much do executive data science jobs pay per year?

As of Jun 24, 2026, the average yearly pay for executive data science in the United States is $93,552.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $120,500.00 per year, depending on experience, location, and employer.

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

To thrive as an Executive Data Scientist, you need deep expertise in statistics, machine learning, and data analysis, typically supported by an advanced degree in a quantitative field. Proficiency with data platforms (such as SQL, Hadoop, or Spark), programming languages (like Python or R), and familiarity with data visualization tools is essential, along with certifications like Certified Analytics Professional (CAP) being advantageous. Strategic vision, leadership, and the ability to communicate complex insights to non-technical stakeholders are vital soft skills. These competencies drive effective data-driven decision-making and ensure alignment between analytics initiatives and business objectives.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Chief Data Officer or Director of Data Science, with salaries exceeding $200,000 annually. These roles typically require extensive experience, advanced skills in machine learning, and leadership capabilities, often complemented by advanced degrees and certifications.

What is Executive Data Science?

Executive Data Science refers to the leadership and management of data science initiatives within an organization. Professionals in this role are responsible for setting the strategic direction for data-driven projects, overseeing data teams, and ensuring that data science efforts align with business goals. They bridge the gap between technical teams and executives, translating analytical insights into actionable business strategies. Typically, Executive Data Scientists have a blend of technical expertise and strong business acumen, enabling them to make high-level decisions that impact the organization’s growth and innovation.

What is the difference between Executive Data Science vs Data Scientist?

AspectExecutive Data ScienceData Scientist
CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic, leadership-focused, often in executive officesHands-on data analysis, modeling, coding in technical teams
Employer & Industry UsageSenior roles in tech, finance, consulting, and large organizationsTech companies, startups, research institutions, various industries

Executive Data Science roles focus on strategic decision-making, leadership, and overseeing data initiatives, while Data Scientists are primarily involved in technical data analysis and modeling. Both roles require strong analytical skills, but Executive Data Scientists combine technical expertise with leadership responsibilities.

Is 40 too late for data science?

Age is not a barrier to becoming an executive data scientist; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this rule to focus on the most impactful variables or tasks to optimize model performance and efficiency.

How does an Executive Data Scientist typically collaborate with other departments to drive data-driven decision making?

Executive Data Scientists frequently work cross-functionally with departments such as marketing, product, finance, and operations to identify key business challenges and opportunities where data can provide strategic insights. They lead or advise interdisciplinary teams, translate complex analytics into actionable recommendations, and often present findings to senior leadership or stakeholders. Building strong relationships and understanding business objectives are crucial, as these collaborations enable the alignment of data science initiatives with organizational goals.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in machine learning, programming, and domain knowledge remain essential for designing and deploying AI solutions effectively.
More about Executive Data Science jobs
What cities are hiring for Executive Data Science jobs? Cities with the most Executive Data Science job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Executive Data Science jobs? States with the most job openings for Executive Data Science jobs include:
What job categories do people searching Executive Data Science jobs look for? The top searched job categories for Executive Data Science jobs are:
Executive Data Science jobs near you
Infographic showing various Executive Data Science job openings in the United States as of June 2026, with employment types broken down into 50% Full Time, 25% Part Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $93,552 per year, or $45 per hour.

Data Science Consultant

GARGI TECHNOLOGIES INC

Manhattan, NY • On-site

Other

Posted 20 days ago

Job description

Job Title: Data Science Consultant (Onsite)

Location: New York (Onsite)
Job Type: Contract / Full-Time

< data-start="2640" data-end="2656">Job Summary

We are seeking a Data Science Consultant to help clients transform their data into actionable insights. The ideal candidate will combine technical expertise with strong business acumen to deliver impactful solutions.

< data-start="2875" data-end="2896">Responsibilities
  • Analyze business challenges and recommend data-driven solutions.
  • Develop machine learning and statistical models.
  • Create executive-level reports and presentations.
  • Collaborate with cross-functional teams and client stakeholders.
  • Build data visualizations and performance dashboards.
  • Ensure data integrity and governance compliance.
  • Support model deployment and monitoring activities.
< data-start="3296" data-end="3316">Required Skills
  • Bachelor''s or Master''s degree in a quantitative field.
  • 4+ years of experience in data science, analytics, or consulting.
  • Strong Python, SQL, and data visualization skills.
  • Experience with machine learning, forecasting, and predictive modeling.
  • Excellent communication and client-facing skills.
< data-start="3622" data-end="3643">Preferred Skills
  • Experience with cloud-based analytics platforms.
  • Knowledge of AI/ML deployment and MLOps practices.

Work Schedule: Monday–Friday, 100% Onsite.
Compensation: Competitive salary, performance bonuses, and comprehensive benefits package.

By the way, if you''re using these for recruiting platforms like Dice, what do you think of the format and level of detail? I can tailor future postings to be more concise, more recruiter-focused, or more technical depending on your preference.

 

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