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Remote Economics Data Science Jobs in Michigan (NOW HIRING)

Munich Re

Data Scientist, AI

Ann Arbor, MI · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Science, or Statistics/Math and Economics double major, or Statistics/Math and Computer Science ...

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 ...

Varsity Tutors

College Economics Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

Adapts instruction using worked problems, graphing exercises, and current economic data analysis to ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Varsity Tutors

College Economics Tutor

Detroit, MI · Remote

$18 - $40/hr

Adapts instruction using worked problems, graphing exercises, and current economic data analysis to ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Varsity Tutors

College Economics Tutor

Kalamazoo, MI · Remote

$18 - $40/hr

Adapts instruction using worked problems, graphing exercises, and current economic data analysis to ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

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All JobsEconomics Data Science JobsRemote Economics Data Science JobsRemote Economics Data Science Jobs in Michigan

Remote Economics Data Science information

Can data science jobs be done remotely?

Remote economics data science jobs are common, allowing professionals to work from anywhere with internet access. These roles often require skills in programming, data analysis, and tools like Python or R, and may involve collaboration through online platforms. Many companies now offer flexible or fully remote positions for data scientists.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. For a remote economics data scientist, focusing on the most impactful variables or data sources can improve model efficiency and accuracy.

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

To thrive as a Remote Economics Data Scientist, you need a strong background in economics, statistics, and data analysis, typically supported by a degree in economics, statistics, or a related field. Proficiency in programming languages like Python or R, experience with data visualization tools, and familiarity with databases or cloud platforms are essential technical skills. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for collaborating remotely and delivering actionable insights. These skills are crucial for accurately interpreting economic data, building predictive models, and driving data-informed decision-making in a remote environment.

What jobs can I get with data science and economics?

With a background in data science and economics, you can pursue roles such as economic analyst, data scientist, financial analyst, policy analyst, or research associate. These positions often require skills in statistical analysis, programming (e.g., Python, R), and understanding economic models, and they are common in finance, government, consulting, and research organizations.

How do remote Economics Data Science professionals typically collaborate with cross-functional teams?

Remote Economics Data Science professionals often work closely with teams in product, engineering, and business strategy through virtual meetings, shared dashboards, and collaborative tools. Communication is key, as they translate complex economic models and data findings into actionable insights for stakeholders with varying technical backgrounds. Regular check-ins, clear documentation, and participation in agile sprints or project cycles help align goals and ensure that data-driven recommendations are integrated into decision-making processes. Adapting to different time zones and building strong virtual relationships are important aspects of effective collaboration in this remote role.

What is a Remote Economics Data Scientist?

A Remote Economics Data Scientist is a professional who analyzes large sets of economic and financial data to extract insights, build predictive models, and support decision-making, all while working from a remote location. They combine expertise in economics, statistics, programming, and data analysis to interpret trends and inform business or policy strategies. Remote Economics Data Scientists often use tools such as Python, R, SQL, and data visualization platforms to communicate findings effectively. Their work can span industries like finance, government, consulting, and academia.

Can I be a data scientist with an economics degree?

A data scientist role often requires strong skills in statistics, programming, and data analysis, which can be gained with an economics degree. Many data scientists have backgrounds in economics, especially if they have experience with tools like Python, R, or SQL, and knowledge of machine learning techniques. Additional certifications or coursework in data science can enhance employability in this field.
What are popular job titles related to Remote Economics Data Science jobs in Michigan? For Remote Economics Data Science jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Economics Data Science jobs in Michigan look for? The top searched job categories for Remote Economics Data Science jobs in Michigan are:
What cities in Michigan are hiring for Remote Economics Data Science jobs? Cities in Michigan with the most Remote Economics Data Science job openings:
Remote Economics Data Science jobs near you

Principal Data Scientist (Remote)

Accident Fund Holdings, Inc.

Lansing, MI • On-site, Remote

Full-time

Re-posted 28 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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