1

Volunteer Risk Quant Jobs in Tennessee (NOW HIRING)

Quantitative analytical skills; able to draw conclusions from numerical data. * Experience with ... Proactive in identifying process improvements, risk mitigation, and inventory optimization.

Voluntary benefits including Critical Illness, Group Accident, and Voluntary Life * Employee Referral Program * Discounts on the GOVX website Pay Range $28.85 - $31.25 hourly AAP/EEO Statement EOE.

Procurement Coordinator

La Vergne, TN · On-site

$28.85 - $31.25/hr

Quantitative analytical skills; able to draw conclusions from numerical data. * Experience with ... Proactive in identifying process improvements, risk mitigation, and inventory optimization.

Procurement Coordinator

La Vergne, TN · On-site

$28.85 - $31.25/hr

Voluntary benefits including Critical Illness, Group Accident, and Voluntary Life * Employee Referral Program * Discounts on the GOVX website Pay Range $28.85 - $31.25 hourly AAP/EEO Statement EOE.

Voluntary benefits including Critical Illness, Group Accident, and Voluntary Life * Employee Referral Program * Discounts on the GOVX website Pay Range $28.85 - $31.25 hourly AAP/EEO Statement EOE.

Data Engineer - Healthcare

Nashville, TN · Remote

$110.60K - $132.80K/yr

Advanced degree in a quantitative discipline such as Mathematics, Economics, Finance, Statistics ... Risk Adjustment, and quality metrics (such as HEDIS). * Experience working with Snowflake Cloud.

Volunteer Risk Quant information

What are the key skills and qualifications needed to thrive as a Volunteer Risk Quant, and why are they important?

To thrive as a Volunteer Risk Quant, you need strong quantitative analysis skills, a solid understanding of financial risk modeling, and typically a degree in mathematics, finance, or a related field. Familiarity with statistical software, programming languages like Python or R, and risk management systems such as Value at Risk (VaR) tools is commonly required. Attention to detail, problem-solving abilities, and effective communication are essential soft skills for translating complex data into actionable insights. These competencies ensure accurate risk assessments and help organizations make informed decisions to mitigate financial risks.

What are the main challenges faced by a Volunteer Risk Quant when working with nonprofit organizations?

As a Volunteer Risk Quant, one of the primary challenges is adapting sophisticated quantitative models to environments with limited data and resources, which is common in nonprofit organizations. You may also encounter varying levels of financial literacy among team members, requiring clear communication of complex risk concepts. Additionally, balancing rigorous risk analysis with the practical needs and constraints of the organization can be demanding, but it offers a unique opportunity to make a tangible impact. Close collaboration with finance, operations, and leadership teams is essential to ensure your insights are actionable and aligned with organizational goals.

What are Volunteer Risk Quants?

Volunteer Risk Quants are individuals who offer their quantitative risk analysis skills on a volunteer basis, typically to organizations or causes that need help assessing and managing financial or operational risks. They use mathematical models and statistical techniques to evaluate the likelihood and potential impact of various risks. These volunteers often help nonprofits, startups, or community projects that may not have the resources to hire full-time risk analysts. Their work can include data analysis, creating risk models, and advising on risk mitigation strategies. By volunteering, they contribute their expertise to support organizations in making informed, data-driven decisions.

What is the difference between Volunteer Risk Quant vs Volunteer Data Analyst?

AspectVolunteer Risk QuantVolunteer Data Analyst
Required CredentialsBackground in risk modeling, statistics, or quantitative analysisProficiency in data analysis, statistics, and data visualization tools
Work EnvironmentNon-profit or volunteer organizations focusing on risk assessmentVarious sectors including non-profits, research, or community projects
Employer & Industry UsageUsed in organizations assessing volunteer safety and risk factorsUsed in organizations analyzing volunteer data for insights and improvements

The main difference is that Volunteer Risk Quant focuses on assessing and modeling risks associated with volunteer activities, requiring expertise in risk analysis and quantitative methods. Volunteer Data Analysts primarily analyze volunteer data to generate insights, often with broader data skills. Both roles support volunteer programs but serve different analytical purposes.

What are the most commonly searched types of Risk Quant jobs in Tennessee? The most popular types of Risk Quant jobs in Tennessee are:
What are popular job titles related to Volunteer Risk Quant jobs in Tennessee? For Volunteer Risk Quant jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Volunteer Risk Quant jobs in Tennessee look for? The top searched job categories for Volunteer Risk Quant jobs in Tennessee are:
What cities in Tennessee are hiring for Volunteer Risk Quant jobs? Cities in Tennessee with the most Volunteer Risk Quant job openings:
Infographic showing various Volunteer Risk Quant job openings in Tennessee as of May 2026, with employment types broken down into 1% As Needed, 14% Full Time, 60% Part Time, 5% Temporary, 18% Contract, and 2% Nights. Highlights an 94% Physical, and 6% Remote job distribution.

Senior Data Scientist - GenAI/Python/AWS/SQL

Unum Group

Chattanooga, TN • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Job description

When you join the team at Unum, you become part of an organization committed to helping you thrive.
Here, we work to provide the employee benefits and service solutions that enable employees at our client companies to thrive throughout life's moments. And this starts with ensuring that every one of our team members enjoys opportunities to succeed both professionally and personally. To enable this, we provide:
  • Award-winning culture
  • Inclusion and diversity as a priority
  • Performance Based Incentive Plans
  • Competitive benefits package that includes: Health, Vision, Dental, Short & Long-Term Disability
  • Generous PTO (including paid time to volunteer!)
  • Up to 9.5% 401(k) employer contribution
  • Mental health support
  • Career advancement opportunities
  • Student loan repayment options
  • Tuition reimbursement
  • Flexible work environments

*All the benefits listed above are subject to the terms of their individual Plans.
And that's just the beginning...
With 10,000 employees helping more than 39 million people worldwide, every role at Unum is meaningful and impacts the lives of our customers. Whether you're directly supporting a growing family, or developing online tools to help navigate a difficult loss, customers are counting on the combined talents of our entire team. Help us help others, and join Team Unum today!
General Summary:
Are you passionate about using AI and advanced analytics to solve complex, high-visibility business problems? Do you thrive in an innovation-driven environment where you can prototype, experiment, and shape the future of AI at scale? If so, this is the role for you.
We are seeking a Senior or Principal Data Scientist to join our innovation hub-a small, agile team tackling the company's most strategic challenges. You'll build POCs, develop end-to-end machine learning and generative AI solutions, and work directly with senior leaders across the enterprise.
What You Bring
Bachelor's in a quantitative field required (Master's/PhD preferred)
6+ years of experience in data science or machine learning
Strong Python and SQL skills
Experience with cloud platforms (AWS preferred; Azure/GCP comparable)
Databricks + PySpark experience is a strong plus
Background in statistical modeling, ML algorithms, and feature engineering
Ability to build automated analytics workflows and work with APIs
Strong communication skills with experience influencing senior stakeholders
Entrepreneurial mindset, curiosity, and comfort working in fast-moving environments
Job Specifications / Qualifications
Education
  • Bachelor's degree in a quantitative field required.
  • Master's or PhD in a quantitative discipline preferred.

Experience
  • 6+ years of professional experience or equivalent relevant work.
  • Proven track record leading end-to-end data science projects with measurable business impact.

Technical Expertise
Core Data Science Capabilities (expert in at least two, strong in others):
  • Programming & Automation:
    • Python required; experience with automation, DevOps practices, APIs, file I/O, and database integrations.
    • Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable).
    • Exposure to object-oriented development and scalable architecture.
  • Data Visualization:
    • Expertise across multiple visualization tools and techniques.
    • Ability to tailor visuals to business use cases and audiences.
  • Statistics & Machine Learning:
    • Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms.
    • Experience leading large-scale modeling projects end-to-end.
    • Familiarity with generative AI approaches is a plus.
  • Data Engineering / ETL:
    • Strong SQL skills; ability to design, debug, and optimize complex queries.
    • Ability to navigate and explore large databases independently.
    • Experience combining internal and external data sources.

Soft Skills & Business Leadership
  • Strong communication skills, including the ability to influence senior leaders.
  • Project management expertise and strong business acumen (financial services experience a plus).
  • Ability to manage multiple concurrent initiatives in a fast-moving environment.
  • Comfortable leading engagements and representing analytics with executive leadership.

Primary Responsibilities
Analytical Solution Development
  • Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
  • Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering.
  • Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs.
  • Evaluate alternative approaches and select appropriate modeling techniques for each use case.

Data Engineering & Preparation
  • Integrate and transform large volumes of data from diverse sources (e.g., DB2, SQL Server, Teradata, APIs) to support analytics and experimentation.
  • Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques.
  • Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance.
  • Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed.

Automation & Deployment
  • Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms.
  • Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes.
  • Play a lead role in operationalizing AI/ML solutions within production environments.

Visualization, Insights & Communication
  • Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences.
  • Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.
  • Translate complex technical work into business-friendly recommendations.

Leadership, Mentorship & Collaboration
  • Coach, mentor, and develop junior data scientists; provide technical guidance and feedback.
  • Provide leadership on data science initiatives, ensuring outputs meet quality standards.
  • Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners.
  • Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members.

Innovation & Research
  • Stay current on emerging statistical methods, machine learning advancements, and generative AI tools.
  • Conduct independent R&D to prototype new approaches and explore innovative solutions for high-visibility business problems.
  • Demonstrate entrepreneurial, self-starter mindset with a strong curiosity and continuous-learning orientation.

#LI-AD1
#LI-Multi
~IN1
Unum and Colonial Life are part of Unum Group, a Fortune 500 company and leading provider of employee benefits to companies worldwide. Headquartered in Chattanooga, TN, with international offices in Ireland, Poland and the UK, Unum also has significant operations in Portland, ME, and Baton Rouge, LA - plus over 35 US field offices. Colonial Life is headquartered in Columbia, SC, with over 40 field offices nationwide.
Unum is an equal opportunity employer, considering all qualified applicants and employees for hiring, placement, and advancement, without regard to a person's race, color, religion, national origin, age, genetic information, military status, gender, sexual orientation, gender identity or expression, disability, or protected veteran status.
The base salary range for applicants for this position is listed below. Unless actual salary is indicated above in the job description, actual pay will be based on skill, geographical location and experience.
$89,400.00-$183,500.00
Additionally, Unum offers a portfolio of benefits and rewards that are competitive and comprehensive including healthcare benefits (health, vision, dental), insurance benefits (short & long-term disability), performance-based incentive plans, paid time off, and a 401(k) retirement plan with an employer match up to 5% and an additional 4.5% contribution whether you contribute to the plan or not. All benefits are subject to the terms and conditions of individual Plans.
Company:
Unum