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Executive Data Science Jobs in Ohio (NOW HIRING)

Principal Data Scientist

Cincinnati, OH · On-site +1

$165K - $249K/yr

Collaborate with other Data Science leaders to establish an operating model for machine ... executive leadership  It's a bonus if you have * Experience in payments, fintech, or financial ...

Data Strategist

Continental, OH · Remote

$115K - $125K/yr

Develop executive dashboards and performance measurement strategies. * Facilitate data governance ... Bachelor's degree in Information Systems, Data Science, Computer Science, or related discipline.

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data ... Master's degree (e.g., MBA, MS Data Science, MS Health Informatics) preferred. Licensure ...

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data ... Master's degree (e.g., MBA, MS Data Science, MS Health Informatics) preferred. Licensure ...

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data ... Master's degree (e.g., MBA, MS Data Science, MS Health Informatics) preferred. Licensure ...

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data ... Master's degree (e.g., MBA, MS Data Science, MS Health Informatics) preferred. Licensure ...

Showing results 41-60

Executive Data Science information

What skills and qualifications are needed to thrive as an executive data scientist?

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 role of an executive data scientist?

An executive data scientist leads data science initiatives within an organization, translating complex data insights into strategic decisions. They often oversee teams, communicate findings to stakeholders, and require strong skills in analytics, leadership, and business acumen, along with proficiency in tools like Python, R, or SQL. Their role involves aligning data projects with organizational goals and ensuring impactful results.

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.

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 are the most commonly searched types of Data Science jobs in Ohio? The most popular types of Data Science jobs in Ohio are:
What cities in Ohio are hiring for Executive Data Science jobs? Cities in Ohio with the most Executive Data Science job openings:
Infographic showing various Executive Data Science job openings in Ohio as of June 2026, with employment types broken down into 52% Full Time, 28% Part Time, and 20% Contract. Highlights an 100% In-person job distribution.

Principal Data Scientist (Cincinnati)

Global Payments Inc.

Cincinnati, OH • On-site

$165K - $249K/yr

Full-time

Posted 14 days ago


Job description

Principal Data Scientist

This position is not eligible for visa sponsorship, now or in the future. Candidates must be a US Citizen or Green Card Holder. The role is remote in the Greater Boston Area only or hybrid 3 days per week in either our Cincinnati, OH or Atlanta, GA office.

We are seeking an experienced and visionary Principal Data Scientist to help scale our Data Science and AI team. In this role, you will collaborate closely with ML software engineers, product managers, and other product delivery teams to build ML models and data‑driven algorithms into robust, scalable, and production‑ready products that optimize the end‑to‑end payment process. You will act as a payment subject‑matter expert and apply strong system and product thinking to create new product concepts, influence and build development roadmaps, design intelligent decision engines, drive cross‑functional initiatives and mentor senior DS/ML engineers. You will balance strategic leadership with hands‑on technical contribution, dividing your time between setting technical direction and actively participating in architecture, design reviews, code reviews, and selected implementation efforts.

What You’ll Own
  • Define the technical vision and strategy for new data‑driven product initiatives with a focus on end‑to‑end payment optimization, aligning them with business goals.
  • Develop scalable and reusable capabilities to power real‑time machine‑learning models (classification, ranking and optimization), enable rapid experimentation at scale and support continuous monitoring of ML products.
  • Oversee and participate hands‑on in the conceptualization, development, production deployment, operation, validation and maintenance of ML models and model update systems.
  • Establish and ensure adherence to best practices for ML modeling; stay abreast of industry trends and emerging technologies in ML and payment optimization, driving adoption of modern tools, frameworks and infrastructure.
  • Foster a culture of innovation, experimentation and collaboration; mentor an elite team of data scientists.
  • Partner with product, engineering, data and compliance teams to integrate ML into products; communicate complex technical concepts clearly to both technical and non‑technical audiences.
  • Collaborate with other Data Science leaders to establish an operating model for machine learning R&D that optimizes end‑to‑end delivery of business value.
What You’ll Bring
  • Bachelor’s or master’s degree in computer science, statistics, mathematics, engineering or related field (Ph.D. preferred).
  • 7+ years in ML research or engineering; 5+ years building large‑scale, real‑time ML systems in production, including significant hands‑on experience.
  • Expertise in machine learning, statistical modeling and data analysis; strong experience across the ML lifecycle and experimentation processes.
  • Proficiency in Python (Pandas, NumPy, scikit‑learn), strong SQL and database experience (NoSQL and/or graph database experience is a plus).
  • Demonstrated ability to lead solution design and execution, translating complex business requirements into actionable technology solutions.
  • Exceptional verbal and written communication skills, with the ability to influence and collaborate effectively across technical and business audiences at all levels, including executive leadership.
Bonus
  • Experience in payments, fintech or financial services.
  • Knowledge of payment systems (authorization lifecycle, tokenization, fraud/risk, real‑time payments).
  • Experience with cloud platforms (AWS, GCP, Snowflake, Databricks, Vertex AI).
  • Agile development experience.
  • Experience in large companies, mature ML teams and/or highly regulated industries.
Team & Culture

Our inclusive and global teams win together every day. We’re proud to have the best minds in the industry and you can learn from them as you grow your career. The people, the energy, the connections – it’s unmatched. Come and be part of an ever‑evolving company and get dynamic opportunities that go beyond borders.

Earnings

For this full‑time position, the good‑faith estimated annual salary range upon hire is $165,300.00–$249,675.00. This range reflects what we reasonably expect to offer based on the role’s responsibilities, level and geographic location. The actual starting salary will be determined by a candidate’s experience, job‑related skills and relevant education or training. Please note that changes in work location may impact the final offered salary.

EEOC Statement

Worldpay is an equal‑opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status and other protected characteristics. The EEO is the Law poster is available here. If you are made a conditional offer of employment and will be working in the United States, you will be required to undergo a drug test. Reasonable accommodations will be provided for individuals with qualified disabilities both during the hiring process and to allow the individual to perform the essential functions of the job, if hired.

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