1

Data Analyst Machine Learning Jobs in Texas (NOW HIRING)

Senior Machine Learning Scientist

Dallas, TX · On-site

  • Medical

  • Life

  • Retirement

  • PTO

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable ... Data Analysis: Analyze large, diverse data sets to identify patterns, trends, and insights that ...

Machine Learning Engineer

San Antonio, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Knowledge of data preprocessing and feature engineering * Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical ...

Data Scientist

San Antonio, TX · On-site

$110 - $150/hr

  • Medical

  • Retirement

Develop and deploy analytics, machine learning, natural language processing, and AI solutions that ... Perform data acquisition, ETL, exploratory data analysis, data preparation, feature engineering ...

Data Scientist

San Antonio, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

SIMILAR CAREER TITLES Data Analyst, Machine Learning Engineer, Data Engineer, Business Intelligence Analyst, Artificial Intelligence Specialist, Statistician, Predictive Modeler, Research Scientist ...

Showing results 41-60

Data Analyst Machine Learning information

What is a data analyst machine learning?

A Data Analyst Machine Learning job involves analyzing large datasets to extract insights and support decision-making using machine learning techniques. Professionals in this role clean, preprocess, and visualize data while building and evaluating predictive models. They work with programming languages like Python or R, use tools such as SQL and Tableau, and apply statistical methods to uncover patterns. This role bridges data analysis and machine learning by transforming raw data into actionable insights. Typically, they collaborate with data scientists, engineers, and business stakeholders to drive data-driven strategies.

What are the key skills and qualifications needed to thrive in the data analyst machine learning role?

To thrive as a Data Analyst Machine Learning, you need strong analytical skills, a background in statistics or mathematics, and experience in data preprocessing, model building, and evaluation. Familiarity with programming languages such as Python or R, experience with machine learning libraries (like scikit-learn or TensorFlow), and relevant certifications (such as Google Data Analytics or AWS Certified Machine Learning) are highly beneficial. Effective communication, problem-solving, and collaboration skills help distinguish top performers in this role. These abilities are crucial for transforming raw data into actionable insights, presenting findings clearly, and driving data-informed decisions in business settings.

What are the typical career progression opportunities for someone in a data analyst machine learning role?

Many professionals begin as Data Analysts with a focus on machine learning and, as they gain experience, can advance to roles such as Machine Learning Engineer, Data Scientist, or Analytics Manager. Career growth often involves taking on more complex projects, leading analytical teams, and contributing to strategic decision-making within the organization. Expanding your expertise in advanced machine learning techniques, big data tools, and business acumen can open doors to leadership positions. Additionally, working cross-functionally with engineering, product, and business teams provides valuable exposure and opportunities for further advancement.

What is the salary of data analyst in AI ML?

The average salary for a Data Analyst specializing in AI and Machine Learning typically ranges from $60,000 to $100,000 annually, depending on experience, location, and industry. Professionals with skills in Python, R, SQL, and machine learning tools tend to earn higher salaries, especially in tech hubs and companies focusing on AI projects.

What are the most commonly searched types of Data Analyst Machine Learning jobs in Texas?

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

What job categories do people searching Data Analyst Machine Learning jobs in Texas look for?

The top searched job categories for Data Analyst Machine Learning jobs in Texas are:

Infographic showing various Data Analyst Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer, Wallet Intelligence and Machine Learning

Apple, Inc.

Austin, TX • On-site

Other

Re-posted 15 hours ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Are you motivated to protect users and their accounts while delivering the best possible customer experience? Come join the Wallet Intelligence and Machine Learning team, where we help secure users' digital lives across Apple's devices without sacrificing privacy. Machine Learning Engineers here build analytical solutions and think deeply about where they fit into a larger system, staying ahead of fraud and applying the best privacy-preserving and fraud-prevention methods available to make Apple products, and especially Apple Pay and Apple Wallet, the safest platform people can use.
The On Device Insights team at Apple develops machine learning models that run directly on users' devices to protect them from fraud, holding themselves to an exceptionally high bar for privacy. As part of the Wallet Intelligence and Machine Learning team, you will help secure users' digital lives across Apple's devices - including Apple Pay and Apple Wallet - without sacrificing privacy. This is a mission-driven team that thrives on hard problems, healthy skepticism, and open collaboration.
Description
We are looking for a Machine Learning Engineer to help develop and launch on-device technologies that keep our users safe, working closely with engineering, security, program management, and business partners.
Our work is applied and pragmatic by necessity. Models must run in real time and in the background on the device without slowing down something as simple as an in-app purchase, which means designing within real constraints like model size, inference budgets, and memory. Because we often need to anticipate fraud rather than react to each new pattern as it appears, we have to be proactive and think ahead. This role is a chance to take ownership of a problem area, build a system-wide understanding of where our models fit, and apply your expertise in machine learning in an innovative and fast-moving environment.
If you're energized by ambiguity, motivated by a meaningful mission, and the kind of person who digs beneath the surface and questions your own assumptions before forming a recommendation, we'd love to hear from you.
Minimum Qualifications
Experience with machine learning methods such as classification, clustering, and anomaly detection.
Strong programming skills in one or more languages such as Python, Scala, or Java.
Experience processing and analyzing data at scale using distributed data or compute frameworks.
Ability to communicate the results of analysis clearly and succinctly to a range of audiences.
Experience delivering results on ambiguous, loosely defined problems, working with others.
Rigorous analytical thinking, including the ability to question assumptions, reason through a problem, and justify a recommendation with sound evidence.
Preferred Qualifications
Experience deploying machine learning in resource-constrained or real-time environments, such as on-device deployment, model compression, or optimizing for inference budgets.
Experience with distributed data and compute frameworks such as Spark, Ray, or Daft.
Familiarity with privacy-preserving machine learning techniques.
Background in fraud detection, risk modeling, or security-focused machine learning.
Familiarity with iOS development.
We're open to a range of specializations and are excited by candidates who bring a differentiating strength to the team, whether that's a research background, deep systems thinking, or expertise we don't yet have. Tell us what you'd add.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976