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Credit Risk Data Science Jobs in Beechgrove, TN (NOW HIRING)

Demonstrated success delivering cross-functional data science projects with measurable impact. * Strong project management skills, including scoping, planning, and risk mitigation. * Ability to ...

Experience: 10+ years of experience in data science, machine learning, healthcare analytics ... Understanding of healthcare data sensitivity, PHI protection, explainability, model risk, clinical ...

Data Engineer

Murfreesboro, TN · On-site

$103K - $123K/yr

ABOUT US Ascend is the largest credit union in Middle Tennessee and one of the largest credit ... Bachelor's Degree Information Systems, Data Engineering, Data Science, or a related field is ...

Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and ... Advanced degree in life sciences, pharmacy, nursing, or medicine (PharmD, MD, MSc, or equivalent)

Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and ... Advanced degree in life sciences, pharmacy, nursing, or medicine (PharmD, MD, MSc, or equivalent)

... scientific, and test facilities, including wind tunnels (aerospace, DoD, automotive, motorsports ... The software team drives all data acquisition and control room functionality. This includes reading ...

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Credit Risk Data Science information

See Beechgrove, TN salary details

$32.6K

$100.4K

$174.1K

How much do credit risk data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for credit risk data science in Beechgrove, TN is $100,366.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,700.00 and $123,800.00 per year, depending on experience, location, and employer.

What is credit risk data science?

Credit Risk Data Science is a specialized field that uses statistical analysis, machine learning, and data modeling techniques to assess and predict the likelihood that a borrower will default on a loan or credit obligation. Professionals in this field analyze large datasets from financial transactions, credit reports, and market trends to develop models that help financial institutions make informed lending decisions. Their work helps manage risk, set appropriate interest rates, and comply with regulatory standards. By leveraging advanced analytics, credit risk data scientists play a crucial role in minimizing losses and maximizing profitability for banks and lenders.

What skills and qualifications are needed to thrive as a credit risk data scientist?

To thrive as a Credit Risk Data Scientist, you need strong analytical skills, proficiency in statistical modeling, and a solid background in finance, mathematics, or a related field, often supported by an advanced degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of credit risk modeling tools such as SAS or SQL are typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These abilities are crucial for building accurate risk models, informing strategic decisions, and ensuring regulatory compliance in financial institutions.

How does a credit risk data scientist typically collaborate with other teams within a financial institution?

Credit Risk Data Scientists often work closely with credit analysts, risk managers, and IT professionals to develop, validate, and implement models that assess borrower risk. They frequently participate in cross-functional meetings to translate complex analytical findings into actionable business insights. Collaboration with compliance and regulatory teams is also common to ensure that risk models meet current regulatory standards. Effective communication and teamwork are essential, as the role bridges technical model development and practical risk management decisions.
Infographic showing various Credit Risk Data Science job openings in Beechgrove, TN as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $100,366 per year, or $48.3 per hour.

Full-time

Medical, Retirement

Re-posted 22 days ago


Nissan Motor rating

6.5

Company rating: 6.5 out of 10

Based on 207 frontline employees who took The Breakroom Quiz

40th of 45 rated automakers


Job description

Location(s): Smyrna, TN
Job Schedule: Full-time, Hybrid (4 days on-site)
Education Requirement: Bachelors Degree
Sponsorship: No
Shape the Future of Mobility at Nissan: Launch Your Career, Drive Innovation
Come Drive Innovation with Us. We are currently looking for a Data Scientist to join our team in Smyrna, TN. In this role, you will serve as a highly independent contributor responsible for leading large, cross-functional data science initiatives that deliver measurable business value across the MZK organization. The Data Scientist owns end-to-end execution-from problem framing and solution design to model development, validation, and deployment-while partnering closely with stakeholders, product owners, and technical teams.
The Data Scientist combines strong technical expertise in statistical modeling and machine learning with solid business acumen to translate complex operational challenges into scalable analytical solutions. The role operates with a high degree of autonomy in project execution and decision-making, while collaborating with senior data scientists on more complex or ambiguous problems.
In addition to hands-on delivery, this role contributes to team capability by mentoring junior members and reinforcing best practices, though it does not define enterprise-wide standards or long-term data science strategy.
A Day in the Life:
  • Partner with stakeholders and data product owners to translate complex or ambiguous business challenges into structured data science use cases.
  • Lead exploratory data analysis (EDA), data preparation, and feature engineering across diverse data sets.
  • Design, develop, and validate predictive, descriptive, and forecasting models using advanced statistical and machine learning techniques.
  • Apply best practices such as cross-validation, backtesting, and drift monitoring to ensure model reliability.
  • Build end-to-end analytical solutions using tools like Python, R, SQL, Power BI/Tableau, and cloud platforms (AWS, Snowflake).
  • Collaborate with IS/IT and data engineering teams to prepare data pipelines, integrate data sources, and support scalable deployment.
  • Translate technical findings into clear, actionable insights for both technical and non-technical audiences.
  • Lead proof-of-concept (POC) initiatives to evaluate emerging technologies and drive innovation
  • Contribute to governance, documentation, and best practices to ensure consistency and reproducibility.
  • Develop domain expertise across MZK functions to enhance solution relevance and impact.

On the project side, you will:
  • Lead end-to-end delivery of large-scale, cross-functional data science projects.
  • Facilitate solution design workshops, technical reviews, and stakeholder discovery sessions.
  • Define project scope, timelines, and deliverables while managing dependencies and risks.
  • Create structured documentation including workflows, data dictionaries, and modeling artifacts.
  • Monitor progress, ensure alignment to business objectives, and proactively address challenges.

Who We're Looking for:
Required:
  • Bachelor's degree in Business Analytics, Data Science, Operations Research, Mathematics, Statistics, or related field (or equivalent certification).
  • 3+ years of hands-on experience in data science, machine learning, or advanced analytics.
  • Strong expertise in Statistical modeling, machine learning, and predictive analytics.
  • Strong expertise in Python, R, SQL, and data visualization tools (Power BI, Tableau).
  • Strong expertise in Cloud platforms such as AWS, Snowflake, or Azure.
  • Experience designing and validating models using techniques such as time-series cross-validation and backtesting.
  • Proven ability to work with large, complex datasets (structured and unstructured).
  • Demonstrated success delivering cross-functional data science projects with measurable impact.
  • Strong project management skills, including scoping, planning, and risk mitigation.
  • Ability to translate complex problems into analytical solutions and communicate insights clearly.
  • Highly organized, detail-oriented, and capable of managing multiple priorities.

Desired:
  • Master's degree (MS/MBA) in Analytics, Statistics, Mathematics, Operations Research, or related field.
  • 5+ years of data science experience.
  • Experience with big data tools and platforms (e.g., Hadoop, Spark)
  • Familiarity with Agile methodologies.
  • Experience with MLOps tools and model deployment frameworks
  • Strong cross-functional business acumen, especially within manufacturing, supply chain, or procurement domains.
  • Experience collaborating with IS/IT and data engineering teams on data architecture and pipelines.
  • Strong communication and stakeholder management skills across all levels of the organization.
  • Proven experience leading teams or large-scale initiatives with multiple workstreams.

What You'll Look Forward to at Nissan:
Career Growth and Continuous Learning Opportunities: Benefit from diverse career paths, cross-departmental moves, and innovative learning platforms. Enhance your skills through seminars, leadership training, and tuition reimbursement programs, all while playing a vital role in shaping the future of transportation. From day one, you'll have the support to tackle challenges and contribute to impactful solutions across our organization.
Rewards: Be supported with a Comprehensive Benefits Package, including medical, mental health, parental leave, retirement savings & unique Nissan perks, including discounts on lease vehicles as part of our Employee Lease Program and a Vehicle Purchase Program (VPP). For more information, access our Nissan Benefits Overview Guide.
Nissan is committed to a drug-free workplace. All employment is contingent upon the successful completion of drug and background screenings in accordance with Nissan policies and in compliance with federal, state, and local laws, including the California Fair Chance Act and the Los Angeles County Fair Chance Ordinance. Nissan will consider qualified candidates with arrest or conviction records for employment in a manner consistent with these laws.
It is Nissan's policy to provide Equal Employment Opportunity (EEO) to all persons regardless of race, gender, military status, disability, or any other status protected by law. Candidates for this position must be legally authorized to work in the United States and will be required to provide proof of employment eligibility at the time of hire; Nissan uses E-Verify to validate employment eligibility.
NISSAN FOR EVERYONE
People are our most valuable assets, and diversity and inclusion are the key to maximizing the power of each individual member of our team. When everyone belongs, the power of NISSAN is undeniable. Our Corporate Diversity Initiative aims to improve business results by ensuring that our workplace and core businesses meet the unique needs of our employees and customer base.
Nissan is committed to creating a culture where everyone belongs and employees, customers, and partners feel respected, valued, and heard. We have over 10 Business Synergy Teams (BSTs) across the U.S. and Canada that connect employees - with shared characteristics or interests - build allies, and foster a company culture where all employees feel supported and included.
Nissan also values inclusion in all areas of our business as we strive to mirror the diversity of our customer base and the communities where we do business. We are committed to procuring innovative goods and services, retailing our products and communicating from a diverse perspective which will help us continue to offer our customers competitively designed, market-driven products.
Join us as we carry our commitment to diversity and inclusion into the future.
Smyrna Tennessee United States of America

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