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Executive Data Science Jobs in Georgia (NOW HIRING)

Home Depot

DATA SCIENCE MANAGER

Atlanta, GA · On-site

As a Data Science Manager, you will provide executive summaries to all levels of the organization and leverage your business knowledge and network to identify opportunities to leverage data science ...

KPMG

Manager, Data Science

Atlanta, GA · On-site

KPMG is currently seeking a Manager, Data Science to join our Consulting practice. Responsibilities ... Communicate results to executive level audiences. * Leverage deep technical knowledge to build ...

Home Depot

Data Science Manager - GenBI

Atlanta, GA · On-site

As a Data Science Manager, you will provide executive summaries to all levels of the organization and leverage your business knowledge and network to identify opportunities to leverage data science ...

AT&T

Lead Data Scientist

Atlanta, GA · On-site

$171.60K - $257.40K/yr

The role also involves working with large, complex data sets and executing core data science ... Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less ...

AT and T

Lead Data Scientist

Atlanta, GA · On-site

$171.60K - $257.40K/yr

The role also involves working with large, complex data sets and executing core data science ... Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less ...

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Executive Data Science information

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How much do executive data science jobs pay per year?

As of May 28, 2026, the average yearly pay for executive data science in Georgia is $78,994.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $101,700.00 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.

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.

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.

What are the most commonly searched types of Data Science jobs in Georgia? The most popular types of Data Science jobs in Georgia are:
What are popular job titles related to Executive Data Science jobs in Georgia? For Executive Data Science jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Executive Data Science jobs in Georgia look for? The top searched job categories for Executive Data Science jobs in Georgia are:
What cities in Georgia are hiring for Executive Data Science jobs? Cities in Georgia with the most Executive Data Science job openings:
Executive Data Science jobs near you
Manager, Data Science

Manager, Data Science

Broughton Partners

Savannah, GA

Full-time

Posted 7 days ago

Job description

As Manager, Data Science, you will lead our data science function, building predictive models and delivering strategic insights that drive business decisions across Marketing, Operations, and Executive leadership. Your primary focus will be transforming our rich data (Salesforce, Snowflake, call center platforms) into actionable intelligence—lead scoring, conversion forecasting, marketing attribution, call center performance optimization as some examples. You will manage a small team, collaborate with Marketing's Intelligence Director on shared priorities, and operate with significant autonomy to define our analytics roadmap.

  1. Build and deploy predictive models that drive business decisions: lead scoring, conversion forecasting, marketing attribution, fraud detection, capacity planning
  2. Manage and mentor a team of 2 direct reports (Senior Data Analyst and Data Analyst). Develop team capabilities and match work to strengths.
  3. Partner with Marketing Intelligence Director (Marketing org) on shared analytical priorities to maintain one version of truth while respecting organizational swim lanes
  4. Present strategic insights and recommendations to executive leadership monthly, demonstrating measurable business impact (conversion improvement, ROI optimization, cost savings)
  5. Define and own the analytics roadmap—identify what questions the business should be answering and proactively surface insights, not just respond to requests
  6. Collaborate with Data Engineering team to prioritize data quality improvements, ETL enhancements, and infrastructure needs
  7. Establish standardized metrics and methodologies across the organization. Participate actively in Data Governance Council to resolve cross-functional conflicts
  8. Operate with autonomy in defining priorities, methodology, and stakeholder engagement while reporting to Director of Data Operations & Analytics
  9. Other duties as assigned

Education: Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field required. Master's degree preferred or equivalent combination of education and experience.

Work Experience: Minimum of 5-8 years of data science or analytics experience with increasing responsibility. At least 2 years leading analytical initiatives or managing/mentoring analysts or data scientists.

Skills Needed: Expert-level proficiency in SQL, Python, or R, and cloud data platforms (Snowflake preferred). Proven ability to build predictive models (regression, classification, time series) that influenced business strategy. Strong stakeholder management and executive communication skills. Experience in marketing analytics (attribution, ROI), call center operations, or lead-generation business models is strongly preferred.

Licenses or Certification: Not required, but relevant certifications (AWS Certified Machine Learning, Google Professional Data Engineer, or similar) are a plus.


Physical Requirements

Standing, walking, sitting, repetitive movements and use of mechanical controls, such as a keyboard, are frequently required.

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