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Manager Machine Learning Finance Jobs in Texas (NOW HIRING)

AtOrchard LLC

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard ... management, and workforce solutions. Since 2010, we have built high-performing teams and ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... management. Responsibilities Key Responsibilities: * Collaborate with cross-functional teams ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial ... Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk ...

Capital One

Lead Machine Learning Engineer

Plano, TX

$98K - $130K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial ... Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk ...

USAA

AI & Machine Learning Engineer

San Antonio, TX · On-site +1

$103K - $197K/yr

At USAA, our mission is to empower our members to achieve financial security through highly ... Configure, manage, and set up AI/ML infrastructure components in cloud/on-prem environments for ...

Yum Brands

Machine Learning Engineer II

Plano, TX

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... management. Qualifications: * Bachelor's or master's degree in computer science, engineering ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... Ability to collaborate in cross-functional teams (e.g., engineers, product managers) * Knowledge of ...

Yum! Brands

Machine Learning Engineer II

Plano, TX

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... management. Qualifications: * Bachelor's or master's degree in computer science, engineering ...

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All JobsMachine Learning Finance JobsManager Machine Learning Finance JobsManager Machine Learning Finance Jobs in Texas

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 requires strong programming skills, knowledge of financial markets, and experience with tools like Python, R, or specialized ML platforms. It is widely used in finance to automate processes, detect fraud, and enhance decision-making.

Is manager machine learning finance a high paying job?

Manager roles in machine learning within finance are typically high-paying due to the specialized skills required, such as expertise in data science, programming, and financial modeling. Salaries often reflect experience, location, and the complexity of projects, with many positions offering competitive compensation packages. Certifications and advanced degrees can also influence earning potential.

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

TeleWorld Solutions

Plano, TX • On-site

Other

Posted 4 days ago

Job description

Overview
TeleWorld Solutions is seeking a Machine Learning Engineer for our team! As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior and Lead engineers of the Data Science & Tools Team to analyze Samsung's deployed network elements. You will utilize skills to query databases to extract data, use skills in Python or R to analyze data such that you can identify 4G/5G network infrastructure and performance issues and build prediction models, ad-hoc tools, and dashboards to communicate your findings with your team and peers.
TeleWorld Solutions is a strategic wireless engineering and consulting firm offering network operators, OEMs and tower companies turnkey design, optimization, network dimensioning and deployment services.
With the experience of hundreds of thousands of successful implementations, including macro, DAS, Small Cells, and Wi-Fi, the world's leading network operators and OEMs trust our knowledge and experience to plan, perform, troubleshoot, and implement an array of technologies and solutions.
Come join our Veteran-Friendly Team. The Company with Great Benefits and certified as "A Great Place to Work".
Responsibilities
  • 7+ years of professional experience in Data Science, Data Analytics, and/or Data Engineering with abilities to work with large datasets using demonstrated statistical, predictive modeling and machine learning methods.
  • 3-5 years demonstrated experience on designing, deploying, and maintaining large scale ML systems in a production environment.
  • Work closely with the internal and external stakeholders to explore relationships of 4G/5G KPI measurements and targets (KPI, KQI) for 4G/5G RAN product acceptance and performance monitoring.
  • Collaborate with RF engineers, network engineers, data scientists, platform engineers, product teams, and operations stakeholders to ensure ML outputs are technically accurate, interpretable, and operationally useful.
  • Utilize A/B testing, statistical, and machine learning models to build robust mechanism for product & feature performance analysis, for evaluation of new product & SW releases and 3rd party product evaluation.
  • Aid in product & feature performance analysis, evaluation of new product & SW releases and 3rd party product evaluation using analytics/data science to drive intelligent business decisions.
  • Work with the team to proactively define and interpret data/metrics/KPIs, analyze results, and provide insights to determine operational impact, trends and opportunities for all the 4G/5G RAN products.
  • Prototyping use cases, implementing automations, and developing tools to support and augment manual or repetitive efforts.
  • Communicate key findings to stakeholders using visualizations and/or other suitable methods.
  • Excellent verbal and written communication skills to communicate technical and complex concepts in an easy-to-follow progression.
  • Able to compile analysis output and findings into a succinct story for technical and non-technical audiences.
  • Adapt to changes in a dynamic business environment and, support management initiatives.

Qualifications
  • Graduate Degree in Computer Science, Statistics, Data Science or a related Data Engineering with 7+ years of professional experience is preferred.
  • Programming experience: Python & Spark (preferred) and/or other languages such as R , SQL, Hive, Spark, Javascript, Visual Basic, C++, shell scripting in a linux or IDE environment such as VSCODE, Jupyter, RStudio, etc.
  • Cloud Development Experience - AWS/Azure/Google utilizing cloud providers such as Databricks or Snowflake
  • Machine learning expertise: GLM Regression (Linear, Logistic, Multinomial), Decision Tree (including Boosted Trees, Random Forest), kMeans/Hierarchical Clustering, Principle Component Analysis, t-SNE, Neural Networks such as transformers and auto-encoders, Bayesian Regression, and Times Series Modeling.
  • Experience using data with high-volume (1TB+) & high-dimensionality (500+ variables per schema), especially within a big data framework (HaDoop, Citus, MongoDB, etc).
  • Experience performing Data Wrangling, Exploratory Data Analysis (EDA), Correlation Analysis, Statistical Methodologies (distributions, hypothesis testing, confidence intervals) & Significance Testing, A/B Testing.
  • Experience with MLOPS concepts and environments such as MLFLOW a plus.
  • Experience with basic linux administration and software development in a linux environment.
  • Experience in hardware resource management and configuration - CUDA, Docker, KubeFlow, Kubernetes, etc a plus
  • Must possess qualities of being curious and eagerness to learn .
  • Experience with data visualization and ability to quickly grasp statistical methods, and methodologies. Maintain a strong command of current data analytics technology trends, including emerging paradigms and practices.
  • Demonstrated research and problem solving skills via prior work experience. Experience with wireless infrastructure provider and/or operator is desired.
  • Technical knowledge of any wireless technology & procedures including CDMA/EVDO/LTE/Volte and/or 5G a plus.
  • Experience with evaluating service performance trends and proactively defining RAN system performance related issues a plus.
  • Experience of software version control, coding best practices, and use of development management software such as github, bitbucket, etc is desired.
  • Must have a strong work ethic, integrity and work extremely well independently or in a team environment.

Physical/Mental Demands and Working Conditions: The position requires the ability to perform the essential duties and responsibilities in the following environment:
  • Excellent interpersonal and communication skills. Must be skilled in developing and maintaining good working relationships with all appropriate levels within and outside the company.
  • Operate a computer keyboard and view a video display terminal more than 75% of work time in an office work environment

Join Our Veteran-Friendly Team:
Are you a veteran or a veteran spouse with expertise in telecommunications? Join our team at TeleWorld Solutions, where we value your military experience and provide great benefits. We invite all veterans and veteran spouses to bring their skills and dedication to our team.
TeleWorld Solutions is committed to employing a diverse workforce and provides Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.

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