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Manager Machine Learning Finance Jobs in Texas (NOW HIRING)

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

Implement MLOps best practices for model deployment, monitoring, and lifecycle management. * Create ... Machine Learning Expertise: * Clustering and segmentation techniques. * Generalized Linear Models ...

PayPal

Machine Learning Engineer

Austin, TX · On-site

$117K - $138K/yr

We also help merchants connect with their customers, process exchanges and returns, and manage risk ... financial-delivering meaningful value where it matters most.We strive to create a flexible ...

Workiva

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

Workiva

$40/hr

Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

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Manager Machine Learning Finance information

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 Texas?

The most popular types of Machine Learning Finance jobs in Texas are:

What cities in Texas are hiring for Manager Machine Learning Finance jobs?

Cities in Texas with the most Manager Machine Learning Finance job openings:

Manager Machine Learning Finance jobs near you
Infographic showing various Manager Machine Learning Finance job openings in Texas as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, 2% Contract, and 1% Nights. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer II

Irving, TX • On-site

7-Eleven
Food Services and Drinking Places • 10K+ employees
Learn more about 7-Elevenexternal

Full-time

Posted 21 days ago

7-Eleven rating

4.3

Company rating: 4.3 out of 10

Based on 850 frontline employees who took The Breakroom Quiz

Job description

7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation - working hard to be the customer's first choice. 7-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.
Job Summary
We are seeking a talented Machine Learning Engineer to design, develop, and deploy scalable machine learning solutions that drive business value as part of our digital initiatives. As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your expertise in big data technologies, cloud-based data platforms, and machine learning model development, will contribute to the transformation of telemetry data and other large datasets into actionable insights.
Key Responsibilities:
  • Design, develop, test, and deploy machine learning models and data-driven solutions that transform store equipment telemetry data into actionable insights.
  • Work in enterprise environments to build and optimize scalable data pipelines using Python, PySpark, and Azure-based technologies.
  • Process, analyze, and manipulate large structured and unstructured datasets to support analytics and machine learning initiatives.
  • Collaborate with data engineers, data scientists, product owners, and business stakeholders to translate business requirements into technical solutions.
  • Develop, evaluate, and tune machine learning models using appropriate algorithms and statistical techniques.
  • Implement MLOps best practices for model deployment, monitoring, and lifecycle management.
  • Create visualizations, dashboards, and presentations to communicate insights and recommendations to technical and non-technical audiences.
  • Participate in code reviews, technical design discussions, and continuous improvement initiatives.

Required Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
  • 5+ years of experience delivering big data and machine learning solutions in enterprise environments.
  • Strong programming experience in Python and PySpark.
  • Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS), Git, and Azure DevOps.
  • Experience building, training, validating, and deploying machine learning models.
  • Solid understanding of data structures, algorithms, software engineering principles, and distributed computing concepts.
  • Experience working with large-scale datasets and cloud-native architectures.
  • Strong analytical, problem-solving, and communication skills.

Preferred Qualifications:
  • Experience deploying and operationalizing machine learning models in Azure Databricks.
  • Experience with MLOps frameworks and CI/CD pipelines for machine learning workloads.
  • Experience with data visualization tools such as Power BI, Tableau, or equivalent platforms.
  • Experience working with equipment telemetry data or on equipment maintenance projects.
  • Knowledge of containerization technologies and cloud-native application development.

Machine Learning Expertise:
  • Clustering and segmentation techniques.
  • Generalized Linear Models (GLM), Linear Regression, and Logistic Regression.
  • Decision Trees and Random Forests.
  • Gradient boosting techniques including XGBoost.
  • K-Nearest Neighbors (KNN).
  • Support Vector Machines (SVM).
  • Artificial Neural Networks (ANN) and deep learning concepts.
  • Model evaluation, feature engineering, hyperparameter tuning, and performance optimization.

Success Factors:
  • Ability to work effectively in a fast-paced, collaborative environment.
  • Strong ownership mindset and commitment to delivering high-quality solutions.
  • Ability to communicate complex technical concepts to diverse stakeholder groups.
  • Passion for continuous learning and innovation in machine learning and cloud technologies.

If an hourly or salary range is included in this ad it represents the range 7-Eleven in good faith believes is the range of compensation for this role at the time of this posting. The Company may ultimately pay more or less than the posted range. This range is only applicable for jobs to be performed in this state. This range may be modified in the future. No amount is considered to be wages or compensation until such amount is earned, vested, and determinable under the terms and conditions of the applicable policies and plans. The amount and availability of any bonus, commission, long-term incentive compensation, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.
For a general description of all benefits 7-Eleven is offering in the US for the position, please visit this link.
For a general description of all benefits 7-Eleven is offering in Canada for the position, please visit this link.

What 7-Eleven employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About 7-Eleven

Sourced by ZipRecruiter

As the world’s first convenience store, our top priority has always been to give customers the most convenient experience possible to consistently meet their needs. 7-Eleven aims to be a one-stop shop for consumers – a place people can always rely on to deliver what they want, when, where, and how they want it.

Industry

Food services and drinking places

Company size

10,000+ Employees

Headquarters location

Dallas, TX, US

Year founded

1927

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