1

Senior Data Manager Jobs in Ohio (NOW HIRING)

As an Investment Data Management professional, you will serve as the primary liaison between the ... Demonstrated expertise in building relationships, facilitating large meetings, influencing senior ...

Fractional Data Architect

Columbus, OH ยท On-site

$140 - $200/hr

Senior Data Architect Overview Our client is seeking a Senior Data Architect to help define and ... Define and promote best practices for data governance, security, access management, data quality ...

New

Urgent Need SR Data Analyst

Dayton, OH

$83K - $105K/yr

USM Business Systems, established in 1999, is an industry-leading private talent management firm ... Title: Sr. Data Analyst - SQL Location: Dayton, OH Duration: 9 to 12 months+ Top Desired Skills:

Senior Data and Analytics Developer Full Time Perm Salary: $96,600 - $144,900, plus 8% annual bonus ... Develops and manages personal deliverables, timelines and milestones related to assigned projects.

LHH is partnering with a growing organization in the Columbus, OH area to identify a Senior Data ... Pay Details: $90,000.00 to $108,000.00 per year Search managed by: Jessica Robbins Equal ...

Senior Data Scientist - AI

Columbus, OH ยท On-site

$90 - $120/hr

The Senior Data Scientist- AI, contributes to building and developing the organization's data infrastructure and supports the senior leadership with insights, management reports, and analysis for ...

New

Showing results 21-40

Senior Data Manager information

See Ohio salary details

$75.1K

$117K

$175.4K

How much do senior data manager jobs pay per year?

As of Aug 8, 2026, the average yearly pay for senior data manager in Ohio is $116,988.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,300.00 and $130,700.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Data Manager, you need expertise in data management principles, database design, and statistical analysis, usually backed by a degree in computer science, information systems, or a related field. Familiarity with database management systems (e.g., SQL, Oracle), data integration tools, and certifications like CDMP or DAMA are highly valued. Leadership, problem-solving, and effective communication are critical soft skills for managing teams and collaborating across departments. These skills ensure accurate data governance, efficient project execution, and the alignment of data strategy with business goals.

What is the difference between Senior Data Manager vs Data Analyst?

AspectSenior Data ManagerData Analyst
Required CredentialsBachelor's or Master's in Data Science, Business, or related field; experience in data managementBachelor's in Statistics, Data Science, or related field; proficiency in data analysis tools
Work EnvironmentOversees data teams, manages data systems, and ensures data qualityAnalyzes data sets, creates reports, and supports decision-making
Employer & Industry UsageUsed in corporate, healthcare, finance sectors for data governanceCommon in marketing, research, and business intelligence roles

The main difference is that Senior Data Managers focus on overseeing data operations and strategy, while Data Analysts primarily analyze data to generate insights. Senior Data Managers have broader responsibilities in data governance and team management, whereas Data Analysts concentrate on data interpretation and reporting.

What is a senior data manager?

A Senior Data Manager is a professional responsible for overseeing the collection, management, and analysis of large sets of data within an organization. They ensure data quality, integrity, and security, and often lead a team of data professionals such as analysts and data engineers. Senior Data Managers collaborate with IT, business, and analytics teams to support data-driven decision-making and compliance with data regulations. They typically have several years of experience in data management, strong technical skills, and leadership abilities.

How much does a senior data manager get paid?

The average salary for a senior data manager typically ranges from $90,000 to $130,000 annually, depending on experience, industry, and location. They often require strong skills in data analysis, database management, and familiarity with tools like SQL and data visualization software.

What are some typical challenges faced by senior data managers when implementing new data governance policies?

Senior Data Managers often encounter challenges such as resistance to change from stakeholders, integrating new policies with existing legacy systems, and ensuring consistent data quality across departments. Effective communication and cross-team collaboration are crucial to overcome these hurdles, as is providing ongoing training to staff. Additionally, Senior Data Managers need to balance compliance requirements with business objectives to ensure that new policies are both practical and sustainable.
What cities in Ohio are hiring for Senior Data Manager jobs? Cities in Ohio with the most Senior Data Manager job openings:
Infographic showing various Senior Data Manager job openings in Ohio as of August 2026, with employment types broken down into 85% Full Time, 1% Part Time, and 14% Contract. Highlights an 82% In-person, 7% Hybrid, and 11% Remote job distribution, with an average salary of $116,988 per year, or $56.2 per hour.

Senior Data Scientist

Sequoia Financial Group Llc

Cleveland, OH โ€ข On-site

Full-time

Re-posted 21 days ago


Job description

Sequoia Financial Group is a growing Registered Investment Advisor (RIA), headquartered in Northeast Ohio, offering financial planning and wealth management services. At Sequoia, we exist with a singular purpose: to enrich lives. Our values define how we behave and guide us through the pursuit of our purpose to enrich lives. At Sequoia, our core values are:

    • Integrity. We act in the best interests of others by providing an honest, consistent experience for our clients and team.
    • Passion. We pursue our full potential, seeking to continually enhance and evolve our ability to serve our clients and team.
    • Teamwork. We subordinate our egos to work together for the benefit of our clients.

Our promise to team members is that you will grow with us. From experienced advisors to new college grads to transitioning principals, every team member will find Sequoia a place to refine their professional mission, move into new opportunities, go deeper, and lead further. We are built to help you build a career here as a long-term contributor in our work to enrich lives for generations.

*If you are currently on an EAD or STEM OPT Visa that will eventually require sponsorship for the H1B Visa, unfortunately, we are not able to sponsor.

Summary of the position

As part of our expanding Data & AI Office, we seek a highly motivated and hands-on Sr. Data Scientist to build intelligent models that drive personalization, operational efficiency, and strategic decision-making. This role is ideal for someone who thrives in experimentation, iterative development, ambiguity, and building new capabilities from the ground up. The successful candidate will be comfortable operating in an evolving environment where data engineering, data science, and solution development responsibilities may overlap.

The Sr. Data Scientist will develop product-ready models that support Sequoia’s strategic initiatives in client experience, financial planning, operations, and marketing. This individual will work closely with business stakeholders to understand requirements, translate them into data science problems, and deliver actionable insights through robust modeling and experimentation.

Unlike traditional data science roles operating within mature data platforms, this position requires a builder mindset. The successful candidate will help shape the underlying data environment while simultaneously developing analytical solutions and models that create business value.

This hands-on role requires technical depth in Python programming, data science workflows, and a strong understanding of mapping business requirements to data models. The ideal candidate will be highly innovative, comfortable with ambiguity, and eager to learn through experimentation and iteration.

Success in this role requires a willingness to operate across data science, data engineering, and solution development activities while helping build the foundation of Sequoia’s evolving AI and Data capabilities. This is not a narrowly defined data science role within a mature analytics organization.

This role reports directly to the Vice President of Data and Integrations and collaborates closely with the Data Architect, Client Experience, Marketing, and Technology teams.

Responsibilities
  • Develop and deploy predictive and descriptive models using Python and modern data science libraries
  • Translate business requirements into data science problems and design appropriate modeling strategies
  • Build product-ready models that can be integrated into client-facing and internal applications
  • Conduct exploratory data analysis, feature engineering, and model validation
  • Collaborate with stakeholders across departments to understand use cases and deliver insights
  • Embrace iterative development, rapid prototyping, and continuous learning from experimentation
  • Utilize coding accelerators and low-code tools where appropriate to speed up development
  • Document modeling decisions, assumptions, and performance metrics for transparency and reproducibility
  • Work with data engineers and architects to ensure models are scalable and maintainable in production
  • Stay current with emerging techniques in machine learning, generative AI, and financial modeling
  • Partner with data engineering resources to help define, validate, and operationalize data pipelines, data models, and analytics-ready datasets
  • Contribute to the development and evolution of Sequoia’s cloud data and analytics environment
  • Operate effectively in a rapidly evolving AI and data organization where priorities and requirements may change as new opportunities emerge
  • Identify gaps in data, infrastructure, and processes and proactively recommend solutions
  • Balance immediate business needs with long-term platform and analytics objectives
Required Skills/Experience
  • Master’s degree in Statistics, Data Science or Computer Science is strongly preferred
  • Bachelor’s degree from an accredited US college or university in Statistics, Data Science, Computer Science, Mathematics, Engineering or a related field is required
  • 7- 8+ years of experience in data science, machine learning, analytics, data engineering, or related technical roles
  • Proficiency in Python and relevant libraries (e.g., pandas, scikit-learn, NumPy, matplotlib, seaborn)
  • Strong understanding of statistical modeling, machine learning, and data preprocessing
  • Demonstrated ability to map business requirements to data science solutions
  • Experience with iterative development and rapid experimentation
  • Familiarity with coding accelerators or low-code platforms (e.g., Azure ML Studio, H2O.ai)
  • Excellent communication skills and ability to present findings to non-technical stakeholders
  • Strong documentation and organizational skills
  • Experience in financial services, banking, or insurance sectors preferred
  • Demonstrated ability to operate effectively with limited structure and evolving requirements
  • Familiarity with cloud data platforms, data pipelines, and analytics infrastructure
  • Experience working across both data science and data engineering disciplines preferred
Preferred Skills/Experience
  • Exposure to cloud-based data science environments (e.g., Azure ML, Databricks)
  • Familiarity with tools such as Jupyter Notebooks, Git, and MLflow
  • Experience working with Salesforce, Tamarac, eMoney, Fidelity, Schwab, and Box is a plus
  • Experience working in startup, consulting, high-growth, or rapidly evolving environments
  • Experience helping build data platforms, analytics environments, or AI capabilities from early-stage maturity
  • Experience partnering with business and technical stakeholders to define requirements in ambiguous environments
Competencies
  • Builder mindset with a willingness to create processes, frameworks, and solutions where none currently exist
  • Comfortable operating with ambiguity and helping define the path forward
  • Strong problem-solving skills and ability to balance pragmatism with technical rigor
  • Highly innovative and willing to challenge conventional approaches
  • Comfortable learning from failed experiments and pivoting quickly
  • Ability to influence without authority and work effectively across technical and business teams
  • Ability to work independently while maintaining strong communication and alignment with stakeholders

Work Authorization & Sponsorship:
Applicants must be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence or continue employment at any point in time. Unfortunately, we are not able to provide sponsorship.
EEO Statement:
At Sequoia, we value and respect differences in our workforce. We actively encourage everyone to apply. Sequoia is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, genetics, disability, age, veteran status or any other characteristic protected by law.
Working Conditions:
Frequent minimal physical effort such as sitting, prolonged periods working on a computer, standing and walking is required for this role. Depending on location, occasional moving and lifting light equipment and/or furniture may be required. This role may require occasional travel, including travel to client sites, company offices, or industry events, as needed.

Employer Rights:

This job description does not list all of the job duties of the job. You may be asked by your supervisors or managers to perform other duties. You may be evaluated in part based upon your performance of the tasks listed in this job description. The employer has the right to revise this job description at any time. This job description is not a contract for employment and either you or the employer may terminate your employment at any time for any reason.