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Manager Data Analyst Machine Learning Jobs in Lancaster, TX

Lennox International

Sr. Data Scientist

Richardson, TX · On-site

$113K - $148K/yr

Machine Learning & Analytics * Develop and deploy machine learning models and predictive analytics ... Data Management & Collaboration * Merge, manage, and analyze large, complex datasets. * Collaborate ...

Lennox International

Sr. Data Scientist

Richardson, TX · On-site

$113K - $148K/yr

Machine Learning & Analytics * Develop and deploy machine learning models and predictive analytics ... Data Management & Collaboration * Merge, manage, and analyze large, complex datasets. * Collaborate ...

Lennox International

Sr. Data Scientist

Richardson, TX · On-site

$113K - $148K/yr

Machine Learning & Analytics * Develop and deploy machine learning models and predictive analytics ... Data Management & Collaboration * Merge, manage, and analyze large, complex datasets. * Collaborate ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

... management. Responsibilities Key Responsibilities: * Collaborate with cross-functional teams ... Build robust data pipelines and infrastructure to support the training and deployment of machine ...

MCKESSON

Manager, Data Analytics

Irving, TX

Manager, Data Analytics We're looking for someone who can sit between the business and the ... Help shape our AI strategy by identifying where AI and machine learning can add real value, and ...

Yum Brands

Machine Learning Engineer II

Plano, TX · On-site

... management. Qualifications: * Bachelor's or master's degree in computer science, engineering ... Strong analytical and problem-solving skills, with the ability to translate business requirements ...

McKesson

Manager, Data Analytics

Irving, TX · On-site

Manager, Data Analytics We're looking for someone who can sit between the business and the ... Help shape our AI strategy by identifying where AI and machine learning can add real value, and ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · On-site

... management. Qualifications: * Bachelor's or master's degree in computer science, engineering ... Strong analytical and problem-solving skills, with the ability to translate business requirements ...

McKesson

Manager, Data Analytics

Irving, TX

Manager, Data Analytics We're looking for someone who can sit between the business and the ... Help shape our AI strategy by identifying where AI and machine learning can add real value, and ...

Vangard, Inc.

Data Analyst, Senior Specialist

Dallas, TX

$85K - $107K/yr

Develops and manages analytical roadmaps and learning agendas to drive continuous insight ... Perform complex analyses using advanced techniques and machine learning to uncover trends and ...

KPMG

Manager, Data Engineer - PySpark

Dallas, TX · On-site

KPMG is currently seeking a Manager, Data Science Engineer to join our Consulting practice ... analytics and software development processes for natural language processing, machine learning on ...

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Showing results 41-60

All JobsData Analyst Machine Learning JobsManager Data Analyst Machine Learning JobsManager Data Analyst Machine Learning Jobs in Lancaster, TX

Manager Data Analyst Machine Learning information

See Lancaster, TX salary details

$32.2K

$78.3K

$128.9K

How much do manager data analyst machine learning jobs pay per year?

As of Aug 17, 2026, the average yearly pay for manager data analyst machine learning in Lancaster, TX is $78,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,200.00 and $92,000.00 per year, depending on experience, location, and employer.

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

AspectManager Data Analyst Machine LearningData Scientist
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related; experience in machine learningBachelor's/Master's/PhD in Data Science, Statistics, or related; strong programming skills
Work EnvironmentTeam leadership, project management, cross-department collaborationResearch, model development, data exploration
Employer & Industry UsageBusiness analytics, tech companies, finance, healthcareTech firms, research institutions, consulting

While both roles involve data analysis and machine learning, the Manager Data Analyst Machine Learning focuses on leading teams and managing projects, whereas Data Scientists primarily develop models and perform in-depth data research.

Manager Data Analyst Machine Learning jobs near you

Machine Learning Software Engineer II

Cambium Learning Group, Inc.

Dallas, TX • On-site

$96K - $132K/yr

Other

Re-posted 12 days ago

Cambium Learning Group rating

9.5

Company rating: 9.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

10th of 244 rated software companies

Job description

Cambium Learning Group is an award-winning educational technology solutions leader dedicated to helping all students reach their potential through individualized and differentiated instruction. Using a research-based, personalized approach, Cambium Learning Group delivers SaaS resources and instructional products that engage students and support teachers in fun, positive, safe and scalable environments. These solutions are provided through Learning A-Z (online differentiated instruction for elementary school reading, writing and science), ExploreLearning (online interactive math and science simulations, a math fact fluency solution, and a K-2 science solution), Voyager Sopris Learning (blended solutions that accelerate struggling learners to achieve in literacy and math and professional development for teachers), and VKidz Learning (online comprehensive homeschool education and programs for literacy and science). We believe that every student has unlimited potential, that teachers matter, and that data, instruction, and practice are the keys to success in the classroom and beyond.
Job Overview:
We are seeking a talented Machine Learning Engineer II to join our CAI machine learning and scoring development team. In this role, you will be the crucial bridge between applied research and production systems. Working alongside a cross-functional group of mathematicians, computer scientists, psychometricians, and statisticians, you will design and deploy custom machine learning solutions for our clients and internal platforms.
The ideal candidate is a full-stack ML practitioner who is equally comfortable discussing algorithmic design with researchers and architecting scalable, low-latency production systems. You will own the full software development lifecycle-transforming research prototypes into optimized, production-ready solutions using modern AWS infrastructure such as SageMaker, ECS, and Lambda, with an emphasis on high-throughput inference and PyTorch-to-ONNX model optimization.
Job Responsibilities:
  • Full-Lifecycle ML Development: Lead the transition of machine learning models from theoretical prototypes into scalable, high-performance production systems.
  • AWS Cloud Architecture & Deployment: Architect and deploy ML solutions utilizing AWS ECS (Elastic Container Service) for containerized workloads and AWS Lambda for serverless, event-driven inference pipelines.
  • Model & Inference Optimization: Optimize PyTorch models for production deployment by converting them to ONNX formats. Apply advanced inference optimization techniques (quantization, pruning, ONNX Runtime) and memory-efficient attention mechanisms like Flash Attention to minimize latency and maximize throughput.
  • Infrastructure & Engineering Best Practices: Champion infrastructure best practices for machine learning systems, establishing reliable CI/CD pipelines, and ensuring robust, secure, and reproducible deployments across the AWS ecosystem.
  • Algorithm Engineering: Design, develop, and evaluate algorithms that generate descriptive, diagnostic, predictive, and prescriptive insights from both structured and unstructured data.
  • Robust Software Engineering: Write clean, efficient, and well-tested code. Complete rigorous testing, debugging, and documentation to ensure seamless installation and long-term maintenance.
  • Cross-Functional Collaboration: Actively participate in research discussions, requirements gathering, and system design alongside domain experts to build tailored scoring and ML solutions.

Job Requirements:
  • Experience: 2-5 years of industry experience in Machine Learning Engineering, Software Engineering, or Data Science, with a proven track record of architecting and deploying models to production.
  • Cloud & MLOps Infrastructure: Deep, hands-on experience with the AWS ecosystem, specifically AWS ECS and Lambda. Solid understanding of containerization (Docker) and event-driven architectures.
  • Programming Proficiency: Strong proficiency in modern programming languages used in ML (e.g., Python, C++, Java) and familiarity with industry-standard coding practices.
  • ML Frameworks & Advanced Optimization: Hands-on experience with PyTorch and other machine learning libraries (e.g., Scikit-Learn, TensorFlow). Deep understanding of model optimization pipelines, including PyTorch to ONNX conversions, ONNX Runtime, and scaling attention mechanisms (e.g., Flash Attention).
  • Data Systems: Experience working with large-scale computing frameworks, data analysis systems, and relational/non-relational databases.

Nice to Have's:
  • AWS SageMaker: Experience utilizing AWS SageMaker for managed model training and hosting.
  • Advanced LLMOps & Fine-Tuning: Hands-on experience applying modern parameter-efficient fine-tuning methods (such as LoRA and qLoRA) to large language models.
  • AI Agents: Experience building, integrating, and deploying autonomous or semi-autonomous AI agents to automate complex workflows and connect ML models with external tools/APIs.
  • NLP Expertise: Proven experience and familiarity with deep learning technologies applied specifically to Natural Language Processing (NLP) and complex text-based modeling.
  • Cross-Disciplinary Collaboration: Experience collaborating with specialized researchers (e.g., psychometricians, statisticians) to operationalize complex mathematical concepts.
  • Infrastructure as Code: Experience implementing IaC using tools like Terraform or AWS CloudFormation.
  • Model Monitoring: Experience setting up comprehensive model monitoring systems to detect data drift, concept drift, and model degradation in production AWS environments.

To apply for this opportunity, simply click on the "Apply" button and submit a cover letter and resume.
An Equal Opportunity Employer
We are dedicated to fostering a culture that celebrates unique backgrounds, ideas, and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, gender, gender identity/expression, sexual orientation, national origin, protected veteran status, or disability.

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