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Manager Machine Learning Finance Jobs in Mesa, AZ

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$130K - $150K/yr

Sr. Machine Learning Engineer Salary Range: $130k to $150k Our client is seeking a Sr. Machine ... Maximize GPU utilization through efficient memory management, kernel optimization, and parallel ...

Create reinforcement learning environments for software engineering tasks. * Design tasks involving ... Hiring Manager review. Compensation Compensation is output-based , with payment provided per task ...

New

Experience deploying machine learning or generative and agentic AI solutions into production ... Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong ...

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 ...

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Showing results 1-20

Manager Machine Learning Finance information

See Mesa, AZ salary details

$41.7K

$123.3K

$167.7K

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

As of Aug 28, 2026, the average yearly pay for manager machine learning finance in Mesa, AZ is $123,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,800.00 and $166,700.00 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.

ML Machine Learning Engineer

Phoenix, AZ • On-site

InterSources Inc
Recruiting and Staffing Services • 51 - 200 employees

Full-time

Re-posted 23 days ago


Job description

Job Summary:
InterSources Inc is an Award-Winning Global Software Consultancy focused on Digital Transformations across various domains. They are seeking a Machine Learning Engineer to create and deliver technical solutions for their AI/Client Engineering portfolio, collaborating with business teams and technology partners to operationalize model development and drive the adoption of Machine Learning.
Responsibilities:
• Regularly engage with business teams to understand their needs and imperatives and operationalize a framework for end to end of model development life cycle.
• Communication with release manager on product related issues and enhancements.
• Uplift existing system to new Client platform and conduct migration testing Automated transformation and data analysis pipeline to create visualization reports and monitoring
• Capability of implementing REST/function API with various types of database
• Review metadata, provide trouble shooting and change requirement between file batches
• Capability of writing, debugging and compiling codes in Machine learning Operation environment
• More than 70%+ of the time spent on coding and/or hands-on technical implementation of re-usable frameworks to drive adoption of Machine Learning in Client
Qualifications:
Required:
• At least 3+ years of experience in the following areas: Bachelor or Master degree in Computer Science, Computer Engineering.
• Hands on knowledge of JAVA, Python, Rest API, Function API, SQL/Hive QL
• Deep understanding of CI/CD process and tools like Git, Docker, Jenkins, XL Release etc.
• Experience with SQL/NSQL databases (MongoDB, Couchbase, Postgres, Cassandra)
• Knowledge in public cloud platforms like AWS, GCP, and Azure
• Ability to scale to big data framework (Hive, pySpark)
• Ability to work in cross functional teams
• Excellent data presentation and visualization skills
Preferred:
• Nice to have experience with any of the Container technologies
• Kubernetes, Helm, Openshift etc.
• Prefer knowledge on Airflow, MLflow.
Company:
InterSources Inc. solves operational problems where protection, performance, compliance, AI, and workforce capability must work together. Founded in 2007, the company is headquartered in Fremont, USA, with a team of 501-1000 employees. The company is currently Late Stage.

InterSources logo

About InterSources

Sourced by ZipRecruiter

In 2007, Our journey began as pioneers in the realm of technology and security. Since then, InterSources Inc. has evolved into a trusted partner, leading the way in Cloud Security, Cybersecurity, PLG Consulting, Digital Transformation, and Professional Services. With a rich history of excellence and a forward-thinking approach, we continue to secure your digital future and drive innovation. Explore our legacy of success and discover the possibilities that lie ahead.

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

Fremont, CA, US

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