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Manager Machine Learning Finance Jobs in Huntsville, AL

IGNITE

MACHINE LEARNING ENGINEER

Huntsville, AL · On-site

Job Title MACHINE LEARNING ENGINEER Location Huntsville, AL US (Primary) Category Engineering Job Type Full-Time Career Level Experienced (Non-Manager) Education Bachelor's Degree Security Clearance ...

ECS

Sr. Databricks Solutions Architect

Huntsville, AL · On-site

... machine learning, and AI-driven insights, and enjoy working in a consulting environment where ... Support Professional Services and Managed Services initiatives as needed, ensuring billable ...

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All JobsMachine Learning Finance JobsManager Machine Learning Finance JobsManager Machine Learning Finance Jobs in Huntsville, AL

Manager Machine Learning Finance information

See Huntsville, AL salary details

$41.4K

$122.5K

$166.5K

How much do manager machine learning finance jobs pay per year?

As of Aug 17, 2026, the average yearly pay for manager machine learning finance in Huntsville, AL is $122,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,100.00 and $165,500.00 per year, depending on experience, location, and employer.

What does a manager of machine learning in finance do?

A Manager of Machine Learning in Finance oversees teams that develop and implement machine learning models to solve financial problems, such as risk assessment, fraud detection, and algorithmic trading. They coordinate with data scientists, engineers, and business stakeholders to ensure models meet regulatory standards and align with company goals. Additionally, they are responsible for project management, mentoring team members, and staying updated with advancements in both finance and artificial intelligence.

How does a manager of machine learning in finance typically collaborate with cross-functional teams?

A Manager of Machine Learning in Finance often works closely with data scientists, software engineers, financial analysts, and business stakeholders. They are responsible for translating business problems into machine learning solutions and ensuring models meet both technical and regulatory requirements. Regular meetings and clear communication are essential, as the manager must align team efforts with organizational goals, facilitate knowledge sharing, and integrate model outputs into financial decision-making processes. Collaboration also involves coordinating with IT for data infrastructure and with compliance teams to uphold data privacy standards.

What are the key skills and qualifications needed to thrive as a manager of machine learning in finance, and why are they important?

To thrive as a Manager of Machine Learning in Finance, you need strong expertise in machine learning, statistics, and financial analysis, typically supported by a relevant advanced degree and experience in both data science and finance. Familiarity with programming languages like Python or R, cloud platforms, and machine learning frameworks such as TensorFlow or Scikit-learn is essential, along with knowledge of regulatory compliance systems. Exceptional leadership, strategic thinking, and communication skills set top candidates apart by enabling effective team management and cross-functional collaboration. These skills and qualities are crucial to drive innovative solutions, ensure regulatory adherence, and deliver business value in a complex financial environment.

What is the difference between Manager Machine Learning Finance vs Data Scientist Finance?

AspectManager Machine Learning FinanceData Scientist Finance
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or Finance; certifications in machine learning or data analysisBachelor's or Master's in Data Science, Statistics, or related fields; often includes certifications in data analysis or programming
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in financeAnalyzes data, develops models, supports decision-making in finance teams
Employer & Industry UsageFinancial institutions, hedge funds, investment firmsFinancial firms, banks, fintech companies

The Manager Machine Learning Finance oversees teams and projects applying machine learning to finance problems, focusing on leadership and strategy. In contrast, Data Scientists in finance primarily analyze data and develop models to support financial decisions. Both roles require strong technical skills, but the manager role emphasizes team management and project oversight.

Can manager machine learning finance be used in finance?

A Manager of Machine Learning in Finance oversees the development and implementation of machine learning models to improve financial analysis, risk management, and trading strategies. This role involves skills in data science, programming, and finance, and is used to enhance decision-making processes and automate tasks within financial institutions.

What are the most commonly searched types of Machine Learning Finance jobs in Huntsville, AL?

The most popular types of Machine Learning Finance jobs in Huntsville, AL are:

Manager Machine Learning Finance jobs near you

MACHINE LEARNING ENGINEER

Ignite Fueling Innovation

Huntsville, AL

Full-time

Re-posted 18 days ago

Job description

Igniters operate in the world's most demanding environment. Igniters are self-motivated, mission-driven, and relentless in solving the Warfighters' hardest problems. We move fast, think differently, and execute with precision to tackle high-stakes challenges across AI/ML, space and missile defense intelligence, EMSO, advanced analytics, and programmatic domains.

As an employee-owned SDVOSB headquartered in Huntsville, AL, our team delivers mission-critical impact for the Army, Air Force, Space Force, MDA, NASA, DIA, and FBI. Ignite exists to outpace the threat and deliver results that matter in the moments that count. Ignite is currently seeking a driven, detail-oriented Machine Learning Engineer to join our team supporting the Missiles and Space Intelligence Center in Huntsville, AL.

This position is expected to be on-site. The team will work with technologies including: Open source, commercial, and government software packages such as Docker, Python, Jupyter Notebooks, PostgreSQL, and other tools. Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.Responsibilities include, but are not limited to: Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture

Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions. Construct optimized data pipelines to feed ML models; run tests and experiments and document findings. Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.

Write clean, testable, maintainable code in Python and other languages. Job Requirements and Qualifications: A minimum of 12 years of work experience, with 1-3 years of experience working with ML frameworks TS/SCI with ability to obtain CI Polygraph after onboarding. Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.

1-3 years of experience working with ML frameworks. Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling. Solid understanding of the full ML development lifecycle.

Experience working with SQL and NoSQL databases. Experience with both Linux and Windows operating systems. Knowledge of CI/CD and Agile methodologies.

Understanding of software design and system integration. Preferred Qualifications: Experience with petabyte scale data sets Experience with multi-INT analytics Experience deploying, monitoring, and scaling models in production environments Education Requirements: Master's degree in a related field with 12 years of experience or a bachelor's degree in a related field with 17 years of experience. Other Requirements: Must be a US citizen and be able to obtain and hold an active TS/SCI Clearance with CI Polygraph.Responsibilities include, but are not limited to: Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture

Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions. Construct optimized data pipelines to feed ML models; run tests and experiments and document findings. Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.

Write clean, testable, maintainable code in Python and other languages. Job Requirements and Qualifications: A minimum of 12 years of work experience, with 1-3 years of experience working with ML frameworks TS/SCI with ability to obtain CI Polygraph after onboarding. Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.

1-3 years of experience working with ML frameworks. Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling. Solid understanding of the full ML development lifecycle.

Experience working with SQL and NoSQL databases. Experience with both Linux and Windows operating systems. Knowledge of CI/CD and Agile methodologies.

Understanding of software design and system integration. Preferred Qualifications: Experience with petabyte scale data sets Experience with multi-INT analytics Experience deploying, monitoring, and scaling models in production environments Education Requirements: Master's degree in a related field with 12 years of experience or a bachelor's degree in a related field with 17 years of experience. Other Requirements: Must be a US citizen and be able to obtain and hold an active TS/SCI Clearance with CI Polygraph.

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