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Senior Director Data Science Jobs in Ohio (NOW HIRING)

... data science, and reporting and analytics. KEY RESPONSIBILITIES Organizational Strategy & Vision ... Partner with senior leadership to shape strategic pillars and modernize the data stack ...

Director Data & Insights

Columbus, OH · On-site

$120 - $160/hr

... science, and reporting and analytics. KEY RESPONSIBILITIES * Organizational Strategy & Vision ... Partner with senior leadership to shape strategic pillars and modernize the data stack ...

... science, and reporting and analytics. KEY RESPONSIBILITIES * Organizational Strategy & Vision ... Partner with senior leadership to shape strategic pillars and modernize the data stack ...

... science, and reporting and analytics. KEY RESPONSIBILITIES * Organizational Strategy & Vision ... Partner with senior leadership to shape strategic pillars and modernize the data stack ...

Advanced degree in Computer Science, Data Science, Electrical Engineering, or related field, or equivalent experience. * Strong proficiency in Python (PEP8, Google Style Guide, type hints, docstring ...

Opportunity to shape data science strategy and standards* Direct collaboration with senior stakeholders* Leadership and mentorship opportunities* Comprehensive benefits package with health, dental ...

Our success is a direct reflection of the talented and diverse people who make a positive ... partners and senior leadership. * Manages project scope, expectations, and timelines.

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Senior Director Data Science information

What are the key skills and qualifications needed to thrive as a senior director data science, and why are they important?

To thrive as a Senior Director Data Science, you need deep expertise in advanced analytics, machine learning, statistical modeling, and a strong educational background in a quantitative field, often with a master's or PhD. Familiarity with data platforms (like AWS, Azure), programming languages (such as Python, R), and leadership in deploying enterprise-level data solutions is vital, along with experience managing large teams. Exceptional strategic thinking, communication, and stakeholder management skills set top candidates apart in this role. These abilities are crucial for driving data-driven business strategies, leading high-performing teams, and ensuring impactful outcomes at the organizational level.

What does a senior director of data science do?

A Senior Director of Data Science leads and oversees the data science strategy for an organization, managing teams of data scientists, analysts, and engineers. They are responsible for aligning data initiatives with business goals, guiding advanced analytics projects, and ensuring the effective use of data to drive decision-making. This role often involves collaborating with other executives to develop data-driven solutions, establishing best practices, and setting the vision for how data science supports organizational growth.

How does a senior director of data science typically collaborate with other departments within an organization?

A Senior Director of Data Science frequently partners with leaders from product, engineering, marketing, and business strategy to align data-driven insights with organizational goals. They facilitate cross-functional collaboration by translating complex analytics into actionable business recommendations, ensuring that data science initiatives support top-level priorities. This role often leads a team of data scientists while serving as a bridge between technical teams and non-technical stakeholders, fostering a culture of data-informed decision-making throughout the company.

What is the difference between Senior Director Data Science vs Data Science Manager?

AspectSenior Director Data ScienceData Science Manager
ResponsibilitiesOversees multiple teams, sets strategic vision, aligns data science initiatives with business goalsManages day-to-day operations of data science teams, executes projects, and ensures deliverables
Required CredentialsAdvanced degree (Master's/PhD), extensive experience, leadership skillsRelevant degree, experience in managing data projects, technical expertise
Work EnvironmentStrategic, cross-departmental, executive collaborationOperational, team-focused, project management

The Senior Director Data Science typically holds a higher strategic leadership role, overseeing multiple teams and aligning data initiatives with company goals. In contrast, a Data Science Manager focuses on managing teams and executing projects. Both roles require strong technical backgrounds, but the Senior Director emphasizes strategic vision and leadership across departments.

What are the most commonly searched types of Senior Data Science jobs in Ohio? The most popular types of Senior Data Science jobs in Ohio are:
What are popular job titles related to Senior Director Data Science jobs in Ohio? For Senior Director Data Science jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Senior Director Data Science jobs in Ohio look for? The top searched job categories for Senior Director Data Science jobs in Ohio are:
What cities in Ohio are hiring for Senior Director Data Science jobs? Cities in Ohio with the most Senior Director Data Science job openings:
Infographic showing various Senior Director Data Science job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Executive Director, Data Science (Risk Analytics)

J.P. Morgan

Columbus, OH

Full-time

Medical, Retirement

Posted 22 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Join a team where advanced analytics, strong data foundations, and practical decisioning come together to improve outcomes for customers and the firm. You will lead high-impact data science initiatives that strengthen credit and fraud risk performance through better data, better models, and better insights. This role offers the opportunity to set a multi-year vision, build new capabilities, and scale products that directly influence senior decision-making. You will partner closely with leaders and stakeholders to turn ambiguous questions into measurable business outcomes. 

Job summary 

As an Executive Director, Data Science in the Chase 360 team within the consumer risk organization, you will lead a team of data scientists and analytics professionals to deliver insights and decisioning capabilities that materially improve credit and fraud risk outcomes. You will shape and execute a roadmap for durable ("evergreen") data assets and scalable analytics products, from discovery through production. You will work across functions to identify the most important business problems, define success metrics, and translate opportunities into actionable analytical solutions. You will communicate clearly and credibly with both technical teams and senior leaders, balancing tradeoffs to drive timely decisions.

You will be expected to challenge existing paradigms, raise quality and explainability standards, and improve how data becomes insight at scale. The work spans structured and unstructured data, risk monitoring, and enterprise data product thinking - so you can move from strategy to execution while keeping teams aligned and motivated. You will also identify where generative artificial intelligence can responsibly accelerate the analytics lifecycle and improve analyst productivity. 

Job responsibilities

  • Lead and develop a high-performing data science team through clear direction, coaching, and a culture of high standards, curiosity, and continuous learning
  • Define and execute a multi-year vision and roadmap for evergreen data assets, decisioning capabilities, and scalable analytics products that improve credit and fraud risk performance
  • Expand the coverage, quality, and utility of key data assets (for example, income-related data) to support risk decisions and insights
  • Advance data mining and modeling across structured and unstructured data to identify actionable insights and early indicators of consumer and small business stress
  • Reimagine end-to-end transaction categorization to improve quality, explainability, scalability, and speed to availability for downstream risk use cases
  • Lead generative artificial intelligence - enabled innovation across the data science lifecycle (for example, weak-signal discovery, entity and merchant enrichment, sequence understanding, and unstructured-to-structured transformation)
  • Partner with cross-functional stakeholders and risk leadership to prioritize opportunities, define success metrics, and translate business questions into analytical solutions
  • Deliver executive-ready narratives that clearly communicate insights, recommendations, tradeoffs, and expected business impact
  • Drive execution in a fast-paced environment by aligning stakeholders, prioritizing work across initiatives, and delivering against roadmap milestones

Required qualifications, capabilities, and skills 

  • Master's degree in a quantitative field (for example, computer science, statistics, mathematics, physics, or related discipline)
  • Proven experience leading and developing data science teams, including coaching, performance management, and team culture
  • Demonstrated ability to deliver production-grade, data-driven solutions to complex business problems
  • Strong expertise in consumer financial services and applying analytics to risk decisioning (including credit and fraud)
  • Deep knowledge of statistical modeling and data mining methods across structured and unstructured data
  • Strong programming capability in Python and SQL (and/or comparable analytics languages) and experience working with large-scale data
  • Strategic and commercial mindset: ability to frame ambiguous problems, define clear success metrics, and prioritize high-impact work
  • Strong stakeholder management skills and ability to influence senior leaders through sound judgment and crisp storytelling
  • Excellent written and verbal communication skills for technical and non-technical audiences

Preferred qualifications, capabilities, and skills 

  • Doctoral degree in a quantitative field
  • Experience building and scaling analytics "data products" used by multiple teams or functions
  • Hands-on experience applying generative artificial intelligence techniques to analytics workflows (for example, enrichment, classification, or unstructured text processing)
  • Experience improving transaction data quality, categorization, and explainability for downstream analytics or decisioning
  • Experience partnering with model risk management, governance, and control functions to support responsible deployment
  • Track record of delivering executive-level narratives and decision materials tied to measurable outcomes

ABOUT US

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.