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Data Science Phd Jobs in Texas (NOW HIRING)

Data Scientist

Frisco, TX · On-site +1

$104K - $180K/yr

Job Summary The Senior Associate Data Science role at Bread Financial delivers best-in-class ... Master's Degree or PhD in relevant fields. * 5-8 years professional experience in model building ...

Master's Degree with 3+ years or Doctorate (PhD) with 1+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative ...

Lead data science projects in close collaboration with IT, Data Engineering, Application ... Master's or PhD preferred. While degrees in mathematics, computer science, engineering, or other ...

PhD related to AI or a Master's degree in computer science or a related field and 5+ years of experience with GenAI and related technologies including machine learning. data analytics, and ...

KPMG is currently seeking a Data Scientist to join our Audit Technology Alliance organization ... PhD or Master's degree from an accredited college or university in computer science, statistics ...

Showing results 41-60

Data Science Phd information

What are the key skills and qualifications needed to thrive as a data science PhD?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.
What cities in Texas are hiring for Data Science Phd jobs? Cities in Texas with the most Data Science Phd job openings:
Infographic showing various Data Science Phd job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Scientist - Business Process Re-Engineering

Apple Inc.

Austin, TX • On-site

$150 - $210/hr

Other

Re-posted 7 days 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

Data Scientist - Business Process Re-Engineering

Austin, Texas, United States Operations and Supply Chain

Apple is where extraordinary people do their best work. If making a real impact excites you, a career here might be your dream — just be prepared to dream big!Apple's growing supply chain complexity demands innovative approaches beyond traditional analytics. You'll join a team designing and developing advanced analytics solutions using GenAI, Agentic AI, and modern data science methods to drive decisions. You're passionate about turning data into impactful insights, staying ahead of technology trends, and thrive navigating ambiguity in a fast‑paced environment. If this sounds like you, we'd love to talk.

Description

Engage with business teams to identify opportunities through in depth conversations and being able to translate those requirements into technical solutions and drive critical projectsDesign and architect end‑to‑end data science solutions—selecting from established techniques or engineering novel algorithms tailored to complex supply chain business problemsCollaborate with data engineers and infrastructure partners to implement robust solutions and operationalize models.Continuously enhance and evolve deployed solutions through monitoring, feedback loops, and iteration to meet changing business needs with agilityPresent key findings to leadership to evaluate business impact, in non‑technical termsResearch and evaluate emerging technologies—including GenAI, agentic frameworks, and advanced visualization tools—to expand the team's technical capabilities and accelerate innovationChampion a culture of experimentation and continuous learning, bringing innovative and strategic thinking to reporting, business analytics, and AI‑powered automationDevelop custom models, algorithms, and interactive visualizations—including dashboards and self‑service tools—to deliver actionable Supply Chain insights at scaleWrangle and analyze data to identify patterns, trends, and feature engineeringDefine and track key performance metrics to quantify the business value of deployed data science solutions

Minimum Qualifications
  • PhD in Computer Science, Statistics, Applied Math, Data Science, Operations Research or a related field and 5+ years of industry experience OR MS in related field with 8+ years hands‑on industry experience
  • Demonstrated experience in forecasting, optimization, or simulation within supply chain or operations domains
  • Ability to work well in a fast‑paced, iterative environment and deliver projects under timeline pressures
  • Proven experience building and deploying large‑scale data science and machine learning models, including anomaly detection, NLP, and deep learning techniques with MLOps practices, model versioning, and CI/CD pipelines for implementing, deploying and managing production AIML workflows and projects
  • Experience prototyping and developing software in programming languages (Python, etc.) as well as leveraging advanced SQL for data manipulation
  • Experience building out scalable solutions using GenAI technologies with an emphasis on Agentic solutions using MCP servers, agents, and skills
  • Experience with data acquisition tools (e.g. SQL), data mining and data visualization. Strong background in AIML libraries and frameworks such as Scikit Learn, TensorFlow, PyTorch
  • Experience prototyping, developing software and implementing data science pipelines and applications in programming languages (Python/Java/C++)
  • Track record of staying current with industry best practices, rapidly adopting emerging technologies (e.g., LLMs, RAG, vector databases), and building functional prototypes to validate concepts
  • Champion a culture of experimentation and continuous learning, bringing innovative and strategic thinking to reporting, business analytics, and AI‑powered automation
  • Proven ability to own and deliver end‑to‑end projects from scoping through deployment and post‑launch iteration
  • Proficiency with cloud data platforms (e.g., Snowflake), relational databases (e.g., MySQL), interactive front‑end frameworks (e.g., Streamlit, Tableau, ThoughtSpot), and containerization/orchestration tools (Docker, Kubernetes)
  • Working knowledge of predictive modeling and classification algorithms, regression, clustering, and anomaly detection
  • Passionate about understanding and solving problems and exceptional ability to translate complex AI and ML concepts into clear business narratives, with a talent for data storytelling and presenting analysis effectively to influence senior leadership and cross‑functional partners
  • Self‑sufficient with an ability to thrive in an environment of autonomy amidst ambiguity
  • Strong interpersonal and collaboration skills to partner effectively across functions, share knowledge, communicate findings, and integrate diverse feedback
Preferred Qualifications
  • Meticulous attention to detail, data integrity, and data wrangling
  • Ability to get things done, experience in delivering end‑to‑end projects
  • High intellectual curiosity to learn and understand business needs
  • Self‑sufficient with an ability to thrive in an environment of autonomy amidst ambiguity
  • Strong interpersonal and collaboration skills to partner effectively across functions, share knowledge, communicate findings, and integrate diverse feedback

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.

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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