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Machine Learning Finance Jobs in Tennessee (NOW HIRING)

Inovalon

Senior Machine Learning Engineer

Nashville, TN

$118K - $156K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which ... Inovalon invests in associates to help them stay healthy, save for long-term financial goals, and ...

Deloitte

Finance Analytics & AI Manager

Memphis, TN

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ...

Deloitte

Finance Analytics & AI Manager

Memphis, TN · On-site

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ...

LP Building Solutions

Data Scientist

Nashville, TN · On-site

Leveraging advanced analytical techniques, statistical modeling, and/or machine learning, you will ... and finance teams to identify opportunities, develop predictive and prescriptive models, and ...

New

ISHR

AI/ML Architect

Nashville, TN

$70/hr

... machine learning algorithms. • Ensure models are accurate, efficient, and scalable for deployment ... finance, or manufacturing is a plus.

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Machine Learning Finance information

See Tennessee salary details

$22.7K

$84.1K

$123K

How much do machine learning finance jobs pay per year?

As of Jun 13, 2026, the average yearly pay for machine learning finance in Tennessee is $84,074.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,100.00 and $98,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Finance position, and why are they important?

To excel in Machine Learning Finance, you need strong quantitative skills, proficiency in programming (typically Python or R), and a solid background in both finance and machine learning, often supported by a relevant degree such as in computer science, statistics, mathematics, or finance. Familiarity with machine learning libraries (like TensorFlow, scikit-learn), financial modeling tools, and certifications such as CFA or FRM can be highly beneficial. Excellent problem-solving abilities, communication skills, and a collaborative attitude help professionals translate complex data into practical financial insights and work effectively with both technical and non-technical stakeholders. These competencies enable you to create robust predictive models, drive innovation in financial analysis, and ensure sound decision-making in dynamic industry settings.

What are some typical challenges faced by professionals in Machine Learning Finance roles?

Professionals in Machine Learning Finance often encounter challenges such as working with noisy or incomplete financial data, keeping up with rapidly evolving algorithms, and ensuring model compliance with industry regulations. They may also need to bridge the gap between technical model development and practical business needs, communicating complex findings to non-technical teams. These roles typically involve close collaboration with traders, financial analysts, and risk managers to ensure that machine learning solutions are both accurate and actionable. Facing these challenges can be rewarding, offering significant opportunities for skill development and career advancement in a data-driven financial landscape.

What is a Machine Learning Finance job?

A Machine Learning Finance job involves applying machine learning techniques to financial problems such as risk assessment, algorithmic trading, fraud detection, and portfolio optimization. Professionals in this field build predictive models, analyze large datasets, and automate decision-making processes to improve financial performance. They typically work with tools like Python, TensorFlow, and financial datasets to develop AI-driven solutions. These roles require expertise in machine learning, statistics, and financial markets, often blending data science with quantitative finance.

What are the most commonly searched types of Machine Learning Finance jobs in Tennessee? The most popular types of Machine Learning Finance jobs in Tennessee are:
What are popular job titles related to Machine Learning Finance jobs in Tennessee? For Machine Learning Finance jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Machine Learning Finance jobs in Tennessee look for? The top searched job categories for Machine Learning Finance jobs in Tennessee are:
Machine Learning Finance jobs near you
Infographic showing various Machine Learning Finance job openings in Tennessee as of June 2026, with employment types broken down into 48% Full Time, 50% Part Time, 1% Temporary, and 1% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $84,074 per year, or $40.4 per hour.
Sr. Director, Machine Learning Strategy

Sr. Director, Machine Learning Strategy

Dollar General

Goodlettsville, TN • On-site

Full-time

Posted 17 days ago

Dollar General rating

4.0

Company rating: 4.0 out of 10

Based on 4,463 frontline employees who took The Breakroom Quiz

39th of 39 rated national retailers

Job description


Company Overview

General Summary:

This role exists to build, scale, and operationalize Dollar General’s enterprise machine learning capabilities that directly drive measurable business outcomes. The Senior Director owns the ML strategy, platforms, and teams required to move from isolated models to production-grade, governed, reusable ML systems. This leader ensures ML investments are aligned to enterprise priorities, value realization, and responsible AI standards.


Job Details

Duties and Responsibilities:

  • Lead enterprise machine learning strategy spanning applied ML, MLOps, experimentation, and platform capabilities aligned to business priorities.
  • Build, mentor, and scale high-performing ML engineering and data science leaders across centralized and embedded delivery models
  • Own end-to-end lifecycle of ML systems from problem framing and modeling through deployment, monitoring, and continuous optimization
  • Partner with product, IT, security, legal, and business leaders to ensure governed, responsible, and scalable ML adoption.
  • Establish standards for model evaluation, experimentation, monitoring, and value measurement tied to financial and operational impact

Qualifications

Knowledge, Skills and Abilities:

  • Deep expertise in machine learning systems, model development, and production ML architectures
  • Strong understanding of MLOps, model monitoring, experimentation, and CI/CD for ML
  • Proven ability to translate business problems into scalable ML solutions with measurable impact
  • Experience leading senior technical managers and principal-level engineers
  • Strong judgment around responsible AI, model risk, data privacy, and governance
  • Ability to influence executive stakeholders and align cross-functional teams
  • Experience operating ML platforms in cloud-native environments
  • Excellent communication skills bridging technical and non-technical audiences

Work Experience and/or Education:

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
  • Advanced degree (Master’s / MBA) in a quantitative or AI-related discipline preferred
  • 10+ years of experience in machine learning, data science, or applied AI roles
  • 5+ years leading ML engineering or data science teams at scale
  • Demonstrated experience deploying and operating production ML systems

Experience in retail, e-commerce, supply chain, or large-scale consumer data environments preferred

Qualifications:

Knowledge, Skills and Abilities:

  • Deep expertise in machine learning systems, model development, and production ML architectures
  • Strong understanding of MLOps, model monitoring, experimentation, and CI/CD for ML
  • Proven ability to translate business problems into scalable ML solutions with measurable impact
  • Experience leading senior technical managers and principal-level engineers
  • Strong judgment around responsible AI, model risk, data privacy, and governance
  • Ability to influence executive stakeholders and align cross-functional teams
  • Experience operating ML platforms in cloud-native environments
  • Excellent communication skills bridging technical and non-technical audiences

Work Experience and/or Education:

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
  • Advanced degree (Master’s / MBA) in a quantitative or AI-related discipline preferred
  • 10+ years of experience in machine learning, data science, or applied AI roles
  • 5+ years leading ML engineering or data science teams at scale
  • Demonstrated experience deploying and operating production ML systems

Experience in retail, e-commerce, supply chain, or large-scale consumer data environments preferred

Education:UNAVAILABLEEmployment Type: FULL_TIME

What Dollar General employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Dollar General

Sourced by ZipRecruiter

What started as a single store is now a 20+ billion dollar Fortune 119 company. With 140,000+ employees and counting, we’re growing fast and so can you. There are endless opportunities for you, including award-winning training programs and career paths in retail, distribution, transportation or corporate. The possibilities are endless!

Industry

Retail

Company size

10,000+ Employees

Headquarters location

Goodlettsville, TN, US

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