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Data Science Manager Remote Jobs in Ohio (NOW HIRING)

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Lead Data Science Projects * Translate complex business requirements into robust, scalable ... Project Management * Develop and maintain project plans, milestones, and communication strategies ...

Lead Data Science Projects * Translate complex business requirements into robust, scalable ... Project Management * Develop and maintain project plans, milestones, and communication strategies ...

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate)   ... Lead Data Science Projects Translate complex business requirements into robust, scalable technical ...

AI and Data Science Engineer III

Cleveland, OH · On-site +1

$111K - $133K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms ... Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong ...

Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments and conducting testing. * Participate in the development of modeling presentations and present ...

Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments and conducting testing. * Participate in the development of modeling presentations and present ...

Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments and conducting testing. * Participate in the development of modeling presentations and present ...

Act as a liaison between the ML Engineers and Data Science team, managing AI/ML model deployments and conducting testing. * Participate in the development of modeling presentations and present ...

AI and Data Science Engineer III

Cincinnati, OH · On-site +1

$109K - $131K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms ... Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong ...

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Data Science Manager Remote information

What is the salary of a data science manager?

The salary of a data science manager typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Remote positions may offer competitive compensation aligned with industry standards and often include benefits such as bonuses and stock options.

Can a data scientist work fully remote?

Data science managers and data scientists often have the option to work fully remote, especially in companies that support remote work policies. Success in remote roles typically requires strong communication skills, proficiency with collaboration tools, and the ability to manage projects independently.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of results come from 20% of the efforts or features. Data science managers often focus on identifying the most impactful data, models, or features to optimize performance and efficiency in projects.

What does a remote 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.

Is 40 too late for data science?

Age is not a barrier to becoming a data science manager, as skills and experience are more important. Many professionals transition into data science roles later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning. Continuous learning and practical experience can help individuals succeed regardless of age.

What are the key skills and qualifications needed to thrive as a Data Science Manager (Remote), and why are they important?

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 working remotely 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 June 2026, with employment types broken down into 100% Full Time. Highlights an 8% In-person, and 92% Remote job distribution.

Director, Data Science: Data Science Tools

Liberty Information Technology Limited

Columbus, OH • On-site, Remote

Full-time

Posted 5 days ago


Job description

Description

The Data Science Infrastructure organization within USRM is hiring a Senior Technical Professional, Data Scientist to join the Data Science Tools team. This role will focus on improving the end-to-end modeling workflow for USRM Data Science by building internal tools, pipelines, and applications that streamline model development, evaluation, deployment, and iteration. The ideal candidate is highly technical, proactive, and motivated by building systems that help other data scientists work more efficiently.

**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel. **

Responsibilities:

  • Design and build internal tools, pipelines, and applications that improve model development, evaluation, and deployment
  • Own strategy and roadmaps for improving data science workflows and tooling across USRM
  • Design, build, and maintain Python packages used across the organization
  • Evaluate and implement AI agent capabilities in tooling using approaches such as MCP, RAG, PydanticAI, LangChain, or related frameworks
  • Work with workflow and modeling tools such as Luigi, Airflow, Celery, MLflow, H2O, scikit-learn, Optuna, and LightGBM, as well as Python development tools such as Pydantic, FastAPI, uv, ruff, and pytest
  • Promote MLOps and AI agent best practices in collaboration with groups such as Enterprise Data & Data Science
  • Stay current on developments in open-source data science frameworks, MLOps, and agentic coding practices
  • Help shape the direction of the Tools team and contribute to a culture of ownership, collaboration, and continuous improvement

The ideal candidate will have:

  • Professional experience building and maintaining Python-based data science or Machine Learning tooling used by multiple end users or teams
  • Worked with any of the following in a professional setting: Git, Bash/shell scripting, uv, pre-commit, ruff, pytest, or Pydantic
  • Built, deployed, or maintained workflows or pipelines using any of the following: Airflow, Luigi, Celery, Databricks, or MLflow
  • Implemented or supported AI/LLM-based tooling using frameworks such as PydanticAI, LangChain, MCP, or RAG
  • Developed, reviewed, or maintained internal Python packages, APIs, or data science applications using tools such as FastAPI, Streamlit, Dash, NiceGUI, or Plotly
  • Applied agentic AI techniques in day-to-day development and incorporate AI capabilities directly into tools and applications where they create meaningful value for data scientists
Qualifications
  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Ability to establish and build relationships within and outside the organization.
  • Ability to give effective training and presentations to management and other groups.
  • Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
  • Broad knowledge of business drivers and market context.
  • Has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of  8 years of relevant experience.

Employees may apply for a new role after completing 12 months of employment in their current position.

About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/BenefitsLiberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.Fair Chance Notices

  • California
  • Los Angeles Incorporated
  • Los Angeles Unincorporated
  • Philadelphia
  • San Francisco
Employment Type: FULL_TIME