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Remote Data Science Ngo Jobs in Michigan (NOW HIRING)

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

Cisive

Data Engineer

Wyoming, MI · On-site +1

$103K - $124K/yr

... Data Science, Information Systems, or a related field. * (Required) Strong SQL skills and ... Flexible/remote work options.

Vervint

Director of Data Intelligence

Grand Rapids, MI · On-site +1

Director of Data Intelligence | Remote | Michigan or Minnesota Preferred Role Snapshot: * Set the ... Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ...

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Remote Data Science Ngo information

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.
What are the most commonly searched types of Data Science Ngo jobs in Michigan? The most popular types of Data Science Ngo jobs in Michigan are:
What are popular job titles related to Remote Data Science Ngo jobs in Michigan? For Remote Data Science Ngo jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Ngo jobs in Michigan look for? The top searched job categories for Remote Data Science Ngo jobs in Michigan are:
What cities in Michigan are hiring for Remote Data Science Ngo jobs? Cities in Michigan with the most Remote Data Science Ngo job openings:
Remote Data Science Ngo jobs near you
Infographic showing various Remote Data Science Ngo job openings in Michigan as of June 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Principal Data Scientist (Remote)

Accident Fund Holdings, Inc.

Lansing, MI • On-site, Remote

Full-time

Posted 8 days ago

Job description


SUMMARY
AF Group is seeking a Principal Data Scientist with expertise in either Commercial Property or Personal Homeowners insurance to serve as an individual contributor and technical authority on applying advanced analytics and machine learning to complex business problems, including pricing, risk selection, and other underwriting challenges. This role owns the end-to-end analytical lifecycle, from problem formulation and model development through deployment, monitoring, and governance. Partners closely with Actuarial, MLOps, and IT to deliver scalable, production-ready solutions. The Principal Data Scientist ensures long-term model performance through rigorous validation, drift monitoring, and audit-ready documentation, while advancing analytical best practices and evaluating emerging techniques relevant to commercial P&C insurance.
RESPONSIBILITIES/TASKS:
  • Acquires, organizes, and cleanses structured and unstructured data.
  • Conducts in-depth analysis to uncover trends, risks, and business opportunities.
  • Applies statistical modeling, machine learning, and advanced analytics to develop predictive and prescriptive solutions.
  • Evaluate solution performance using statistically rigorous methods and measure the impact to business outcomes.
  • Collaborate with MLOps and IT partners to transition solution prototypes from pilot validation into production environments.
  • Ensures ongoing model health through post-deployment monitoring, drift detection, and audit-compliant governance practices.
  • Creates and communicates results to senior level audiences of varying backgrounds, using business-facing presentations, reports, and dashboards.
  • Author and maintain comprehensive technical documentation for data lineage, codebases, results, and production changes.
  • Provides technical and project guidance, including peer review of work, for data science team.
  • Leads the evaluation of new analytic tools and processes.
  • Drives investigation and adoption of advanced machine learning and AI innovations.

EDUCATION:
Bachelor's Degree in Data Science, Statistics, Mathematics, Operations Research, Actuarial Science, Computer Science, Engineering, Physics or related technical field required. Advanced degree preferred.
EXPERIENCE:
10 years of experience in data science or related advanced analytics domains, including research and teaching, with 3+ years of technical leadership.
REQUIRED SKILLS/KNOWLEDGE/ABILITIES
  • 3+ years of experience supporting underwriting functions, including loss modeling, for Commercial Property (preferred) or Personal Homeowners insurance.
  • Demonstrated expertise using Poisson, Gamma, and Tweedie distributions to build loss ratio, pure premium, and frequency-severity loss models for pricing.
  • Extensive experience leveraging supervised learning models (e.g., XGBoost, GLM, etc.) and unsupervised techniques (e.g., K-means, PCA, etc.) to solve complex data science problems.
  • Advanced Python programming skills supporting data science, including scikit-learn and pandas.
  • Proficient data wrangling and ETL abilities using SQL on relational databases.
  • Comfortable explaining machine learning models with partial dependence plots and SHAP values.
  • Ability to conduct experiments e.g., A/B Testing, to evaluate the causal impact of model-driven decisions.
  • Experience using version control tools such as Git and Azure DevOps.
  • Experience working in cloud computing environments such as Azure, AWS, GCP, etc.

PREFERRED SKILLS/KNOWLEDGE/ABILITIES
  • Experience supporting at least one other commercial or personal line outside of Property lines.
  • In-depth understanding of General Liability (aka Casualty), Workers Compensation, or Commercial Vehicle insurance.
  • Knowledge of actuarial concepts and terminology used in pricing and ratemaking.
  • Experience with Claims, Marketing, or Operations functions within P&C insurance settings.
  • Ability to develop Agentic AI solutions to drive autonomous decision-making and task orchestration.
  • Familiarity with causal modeling techniques such as Meta-learners, Causal Forest, Double ML, etc.
  • Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
  • Understanding of NLP concepts such as topic modeling, Word2Vec, sentiment analysis, OCR, etc.
  • Experience programming in the R language.
  • Ability to build interactive dashboards using frameworks such as Plotly Dash, Power BI, Flask, etc.

ADDITIONAL INFORMATION:
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. This job description does not constitute a contract for employment.
PAY RANGE:
"Actual compensation decision relies on the consideration of internal equity, candidate's skills and professional experience, geographic location, market and other potential factors. It is not standard practice for an offer to be at or near the top of the range, and therefore a reasonable estimate for this role is between $137,900 and $231,000."
We are an Equal Opportunity Employer. We will not tolerate discrimination or harassment in any form. Candidates for the position stated above are hired on an "at will" basis. Nothing herein is intended to create a contract.
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