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LexisNexis

Manager Data Science

Raleigh, NC · On-site +1

... for remote locations. ** Are you looking to develop your Data Scientist career? Do you enjoy ... coaching others to achieve high standards? Join us in shaping a more just world. About Us

Mercor

Data Science Expert - Fully Remote

New York, NY · Remote

$70 - $100/hr

Expert Professionals -- AI & Data Science Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close ...

Mercor

Data Science Manager

New York, NY · Remote

$70 - $100/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on data science methodology , statistical inference , and modeling best practices . * Design challenging ...

Paylocity

Manager Data Science

This is a fully remote position, allowing you to work from home or location of record within the U ... Manager Data Science Position Overview The Paylocity Data Science team is focused on building ...

Corvel

Data Science Manager

Irvine, CA · On-site +1

The Manager Data Science is responsible for architecting, building, and deploying production-grade ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Design, build ...

College Board

Data Scientist, Data Science Team

This is a fully remote role. Candidates who live near CB offices have the option of being fully ... This is a full-time position About the Team The Data Science team provides critical insights and ...

Zenlaw

Data Scientist (Remote)

New York, NY · On-site +1

Our full-stack Data Science Team uses Python for research and development. Our wide range of ... Due to the remote nature of this role, we are unable to provide visa sponsorship.

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How much do remote data science ngo jobs pay per year?

As of Jun 23, 2026, the average yearly pay for remote data science ngo in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist at an NGO, and why are they important?

To thrive as a Remote Data Scientist at an NGO, you need strong analytical skills, proficiency in statistics, and a degree in data science, computer science, or a related field. Familiarity with tools like Python, R, SQL, and data visualization platforms, along with experience in cloud-based collaboration or project management systems, is typically required. Excellent communication, problem-solving, and self-motivation are vital soft skills for conveying insights and working independently within dispersed teams. These skills ensure the effective analysis and presentation of data to drive evidence-based decisions that further the NGO's mission.

What are remote data science jobs at NGOs?

Remote data science jobs at NGOs involve using statistical analysis, machine learning, and data visualization to support the organization’s mission from any location. Data scientists in these roles analyze large datasets to inform decision-making, measure impact, and optimize programs. Tasks may include building data dashboards, developing predictive models, and communicating insights to non-technical stakeholders. Working remotely allows professionals to contribute to global causes without being tied to a specific office, making these roles flexible and accessible.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of insights or results come from 20% of the data or features. Data scientists often focus on identifying the most impactful variables or data subsets to improve model performance and efficiency.

Can data science jobs be done remotely?

Data science jobs, including roles at remote data science NGOs, are often performed remotely as they primarily involve analyzing data, programming, and using tools like Python or R. Many companies and organizations offer remote data science positions, requiring strong communication skills and proficiency with cloud-based platforms and collaboration tools.

Is 30 too late for data science?

Age is not a barrier to becoming a data scientist; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is 40 too late for data science?

Remote Data Science roles are open to candidates of various ages, and starting a career in data science at 40 is feasible with relevant skills such as programming, statistics, and experience with tools like Python or R. Many professionals successfully transition into data science later in life by gaining certifications, building portfolios, and continuously learning new technologies.

What are some common challenges faced by data scientists working remotely for NGOs, and how can they be addressed?

Remote data scientists in NGOs often face challenges such as limited access to high-quality data, coordinating with geographically dispersed teams, and aligning technical solutions with organizational goals. Clear communication and regular virtual meetings can help bridge collaboration gaps, while utilizing secure cloud-based data storage ensures access to necessary datasets. Additionally, understanding the NGO's mission and maintaining flexibility in problem-solving can help data scientists deliver impactful insights despite resource constraints.
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Remote Data Science Ngo jobs near you
Director, Data Science: Data Science Tools

Director, Data Science: Data Science Tools

Liberty Mutual Insurance

MA • On-site, Remote

$120K/yr

Full-time

Posted 6 days ago

Liberty Mutual rating

8.9

Company rating: 8.9 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

46th of 261 rated insurance

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.

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/Benefits
Liberty 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

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About Liberty Mutual

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Since 1912, we've grown into the fifth largest global property and casualty insurer based on 2022 gross written premium. We also rank 86 on the Fortune 100 list of largest corporations in the US based on 2022 revenue. ​At Liberty Mutual Insurance we work hard every day to support our customers and our people, so they can protect their families, build their businesses and invest in their futures. We are headquartered in Boston, but our people, our customers and our reach span the globe. So to better serve our global customers and employees, we are organized into three business units.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Boston, MA, US

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