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Data Science Manager Remote Jobs in Ohio (NOW HIRING)

Data Architect

Cleveland, OH · On-site +1

$61.75 - $79.50/hr

These platforms manage massive collections of economic time-series data, historical revisions ... No * Current remote employees will not be guaranteed to keep their remote status with their ...

New

$91K - $109K/yr

Establish standards for data quality, governance, security, and lifecycle management . * Ensure ... Bachelor's orMaster's Degree in Computer Science, Data Science, Engineering, or a related field.

New

Manage projects and direct work of more junior team members. * Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling ...

Manage projects and direct work of more junior team members. * Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling ...

Manage projects and direct work of more junior team members. * Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or more years predictive modeling ...

Showing results 41-60

Data Science Manager Remote information

What does a data science manager do?

A remote Data Science Manager oversees a team of data scientists, analysts, and engineers, ensuring that data-driven projects are successfully executed from a remote location. Their responsibilities include managing project timelines, providing technical guidance, mentoring team members, and aligning data initiatives with business goals. They also coordinate with other departments to implement data solutions, ensure data quality, and communicate results to stakeholders. Working remotely, they use digital tools to collaborate, monitor progress, and maintain team productivity.

What are the key skills and qualifications needed to thrive as a data science manager?

To thrive as a Data Science Manager in a remote setting, you need a robust background in statistics, programming (e.g., Python, R), machine learning, and a related degree, often supplemented by experience leading data teams. Familiarity with data analytics tools like SQL, cloud platforms (AWS, Azure), and project management software is typically required, along with certifications such as Certified Data Scientist or PMP. Strong leadership, communication, and collaboration skills are essential for managing distributed teams and aligning projects with business goals. These skills ensure effective project delivery, foster innovation, and maintain team cohesion in a virtual work environment.

How does a data science manager typically collaborate with cross-functional teams?

As a remote Data Science Manager, effective collaboration with cross-functional teams—such as engineering, product, and business stakeholders—relies heavily on clear communication and efficient use of digital tools. Regular virtual meetings, project management platforms, and shared documentation are essential to align on objectives, share progress, and troubleshoot challenges. Building trust and fostering a culture of transparency helps ensure that remote data science teams stay connected and engaged with broader organizational goals, despite not sharing a physical workspace.

What is the difference between Data Science Manager Remote vs Data Analyst Remote?

AspectData Science Manager RemoteData Analyst Remote
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related field; experience with machine learning and leadershipBachelor's in Data Analysis, Statistics, or related field; proficiency in data visualization and SQL
Work EnvironmentLeads data science teams, manages projects, and develops models remotelyAnalyzes data, prepares reports, and supports decision-making remotely
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceMarketing agencies, retail, finance, and consulting firms

The main difference is that Data Science Managers oversee data science teams and projects, requiring leadership skills and advanced technical knowledge, while Data Analysts focus on analyzing data and generating reports. Both roles can be remote and are in high demand across various industries.

What are popular job titles related to Data Science Manager Remote jobs in Ohio?

For Data Science Manager Remote jobs in Ohio, the most frequently searched job titles are:

What cities in Ohio are hiring for Data Science Manager Remote jobs?

Cities in Ohio with the most Data Science Manager Remote job openings:

Infographic showing various Data Science Manager Remote job openings in Ohio as of August 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 100% Remote job distribution.

$61.75 - $79.50/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

CompanyFederal Reserve Bank of St. LouisThe Data Architect will lead the design and modernization of the data architecture that powers the economic data platforms of St. Louis based Research applications such as FRED. These platforms manage massive collections of economic time-series data, historical revisions, digitized archival documents, and research publications.

This role focuses on designing scalable data platforms, data models, and data governance frameworksto support long-term growth, advanced analytics, and global access to economic data. It will leverage in-depth knowledge of modern data technologies, industry frameworks, data security best practices and emerging innovations in AI/ML and data science to accelerate value, delivery and outcomes for the business.

The Data Architect will partner closely with the Application Architectto ensure seamless integration between data platforms and application services.

Key Responsibilities

  • Define and evolve the target data architecturesupporting economic data systems.
  • Design scalable storage architectures capable of supporting billions of time-series observations and historical revisions.
  • Develop metadata schemas supporting dataset discoverability, lineage, and governance.
  • Standardize dataset structures and metadata across multiple platforms.
  • Implement scalable data processing frameworks capable of supporting growing dataset volumes.
  • Improve indexing and metadata strategies that support dataset search and discovery.
  • Enable advanced analytical capabilities for researchers and developers.
  • Partner with the Application Architect to optimize data access patterns for APIs and applications.

Required Qualifications

  • 7-10+ years of experience in data architecture, data engineering or database design and large-scale enterprise cloud data implementations in complex, highly regulated environments. Deep understanding of modern data technology stacks, cloud data platforms (AWS preferred), and enterprise software solutions.
  • Demonstrated experience designing, architecting and supporting external / public-facing applications with a strong emphasis on scalability, security, availability and performance for external customer-facing platforms. Demonstrated knowledge of and leading adoption of industry best practices in the areas of DataOps and modern data stack tools, data governance, SQL and other query tools and knowledge of data privacy regulations. Industry-related certifications in one or more of the above areas are desired. Demonstrated experience in cloud data architecture skills including designing, architecting and delivering modern cloud data platforms to ingest, process, store and expose data across the enterprise. Expert knowledge of data modeling techniques and tools, data lifecycle management and integration patterns to ensure that data flows are consistent, reliable and reusable across services and solutions.
  • Experience with data storage technologies, partitioning strategies, caching, data access patterns, and robust security strategies enforcing privacy and regulatory requirements including designing standardized approaches for data classification, access control, encryption, retention and auditability.
  • Knowledge of data warehousing concepts and tools, big data technologies, machine learning and AI data requirements.
  • Strong recent hands-on experience with PostgreSQL, including schema design, advanced indexing strategies, partitioning, query optimization, and high-availability configurations, ideally in the context of large-scale time-series.
  • Outstanding communication and collaboration skills, including translating technical topics and risks into business teams. Ability to personalize communication to audience from technologists to executive leadership.
  • Extensive, in-depth experience implementing highly complex technology projects in a cross-functional matrix environment with demonstrated ability to drive consensus and deliver results. Examples of leading through influence and successfully resolving conflicting priorities are required.
  • Candidates with less experience may be considered at a lower job grade or salary.

Preferred Qualifications

  • Experience working with time-series data platforms or analytical datasets.
  • Experience with distributed query engines and large-scale data processing systems.
  • Experience with data catalog and metadata management platforms.
  • Familiarity with economic datasets or research data environments.
  • Experience supporting public data access or research-oriented platforms.

Additional Information

Location(s):

  • The selected candidate willresidewithin a reasonable commuting distance, as defined by the employing Reserve Bank, and will work full-time onsite.
  • Locations:Boston, MA- New York, NY- Philadelphia, PA- Cleveland, OH- Richmond, VA- Atlanta, GA- Chicago, IL- St. Louis, MO- Minneapolis, MN- Kansas City, MO- Dallas, TX- San Francisco, CA
  • Remote Eligible: No
  • Current remote employees will not be guaranteed to keep their remote status with their employing bank.

Salary

Salary for St. Louis: $140,000 - $170,000

  • The listed salary is applicabletothe Federal Reserve Bank of St. Louis.Final offers aredeterminedby factors including the candidate's qualifications, internal alignment considerations, district assignment, and geographic location.

Total Rewards

Bring your passion and expertise, and we'll provide the opportunities that will challenge you and propel your growth-along with a wide range of benefits and perks that support your health, wealth, and life.

In addition to competitive compensation, we offer a comprehensive benefits package all brought together in a flexible work environment where you can find balance:

  • Medical (4 options), Prescription, Dental (3 options), and Vision Insurance with no waiting period
  • 401k/Thrift Plan with generous employer match
  • Employer-funded Pension Plan
  • Paid Vacation/Sick Time and Holidays
  • Flexible Spending Accounts and Healthcare Spending Accounts
  • Life Insurance and Long Term Disability Insurance
  • Tuition Reimbursement (undergraduate and graduate)
  • Parental Leave
  • Free onsite 24/7 Fitness Center including training classes, and locker room / shower facilities
  • Onsite Cafeteria and Coffee Shop
  • Additional Convenience Benefits, Discounts and More...

At the Federal Reserve Bank of St. Louis, we are committed to a strong and resilient economy for all. We prioritize inclusion and strive to be a workplace where all employees can thrive. Learn more about Bank'sculture.

The Federal Reserve Bank of St Louis is an Equal Opportunity Employer. #LI-Onsite

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryInformation Technology Family GroupWork ShiftFirst (United States of America)

The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.

Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.

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