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Data Science Engineer Intern Jobs in Dallas, TX (NOW HIRING)

Qorvo, Inc.

Staff Data Science Engineer

Richardson, TX · On-site

Role Summary We are looking for a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value ...

Qorvo, Inc.

Staff Data Science Engineer

Richardson, TX · On-site

They are seeking a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value across the ...

Black Box

AI Engineer Intern - USA

Plano, TX · On-site

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration ... Science, Artificial Intelligence, Data Science, or similar). * Must have at least 6 months ...

Veryable, Inc.

Platform Engineer Intern

Dallas, TX · On-site

Ownership in the evolution of Veryable's data infrastructure and data warehouse architecture to ... Science, Engineering, or related degree with one quarter or semester left. * Knowledge of ...

Deloitte

Lead AI and Data Science Engineer II

Dallas, TX · On-site

$101K - $133K/yr

Lead AI and Data Science Engineer II Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent ...

Deloitte

Lead AI and Data Science Engineer II

Fort Worth, TX · On-site

$98K - $129K/yr

Lead AI and Data Science Engineer II Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent ...

Black Box

AI Intern - Dallas, TX

Plano, TX · On-site

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration ... in Engineering or a related field (Computer Science, Artificial Intelligence, Data Science, or ...

ANS

Lab Engineer (Intern)

Alvarado, TX · On-site

$18 - $22/hr

Data Recording: Maintain comprehensive documentation of test procedures, observations, and results ... Applicants should be pursuing a degree in geology, civil engineering, environmental sciences ...

Gartner

Director, Data Science

Irving, TX · Remote

  • Medical

  • Retirement

  • PTO

Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value. * Lead a team of data scientists, driving ...

Kaizen Analytix LLC

AI Engineer Internship

Dallas, TX · On-site

$25/hr

The intern will work under the guidance of senior engineers on real project tasks, with a focus on ... Work alongside data scientists and engineers to understand requirements and how they translate into ...

Kaizen Analytix

AI Engineer Internship

Dallas, TX · On-site

$25/hr

The intern will work under the guidance of senior engineers on real project tasks, with a focus on ... Work alongside data scientists and engineers to understand requirements and how they translate into ...

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Data Science Engineer Intern information

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How much do data science engineer intern jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for data science engineer intern in Dallas, TX is $25.14, according to ZipRecruiter salary data. Most workers in this role earn between $20.43 and $28.56 per hour, depending on experience, location, and employer.

What is the difference between Data Science Engineer Intern vs Data Analyst Intern?

AspectData Science Engineer InternData Analyst Intern
Required SkillsProgramming (Python, SQL), machine learning, data modelingData visualization, statistical analysis, Excel skills
Work EnvironmentCollaborates with data engineering and data science teams on model developmentFocuses on data reporting and insights for business decisions
Industry UsageTech, finance, healthcare, where data science projects are commonRetail, marketing, finance, emphasizing data reporting

The Data Science Engineer Intern role involves building and deploying machine learning models, requiring programming and data modeling skills. In contrast, the Data Analyst Intern focuses on analyzing data and creating reports for business insights. Both roles are entry-level internships but serve different functions within data teams.

What are the most commonly searched types of Data Science Engineer jobs in Dallas, TX?

The most popular types of Data Science Engineer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Data Science Engineer Intern jobs?

Cities near Dallas, TX with the most Data Science Engineer Intern job openings:

Data Science Engineer Intern jobs near you
Infographic showing various Data Science Engineer Intern job openings in Dallas, TX as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $52,298 per year, or $25.1 per hour.

Staff Data Science Engineer

Qorvo, Inc.

Richardson, TX • On-site

Full-time

Re-posted 26 days ago

Qorvo rating

8.3

Company rating: 8.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

Job description

Qorvo (Nasdaq: QRVO) supplies innovative semiconductor solutions that make a better world possible. We combine product and technology leadership, systems-level expertise and global manufacturing scale to quickly solve our customers' most complex technical challenges. Qorvo serves multiple high-growth segments of large global markets, including consumer electronics, smart home/IoT, automotive, EVs, battery-powered appliances, network infrastructure, healthcare and aerospace/defense. Visit www.qorvo.com to learn how our innovative team is helping connect, protect and power our planet.
Role Summary
We are looking for a Staff Data Science Engineer to lead the design and delivery of scalable data science, machine learning, and analytics solutions that create measurable business value across the enterprise. This role sits at the intersection of data science, data engineering, analytics engineering, and AI productization. The right person will pair strong technical depth with practical business judgment, helping turn complex data into decisions, tools, and systems that improve operations, reduce cost, accelerate insight, and scale AI adoption.
This is a senior individual contributor role for someone who can operate as a technical leader across functions, influence stakeholders from engineers to executives, and build robust solutions in environments where data quality, governance, speed, and return on investment all matter.
In the current integration environment, this role must also work effectively within approved collaboration and information-sharing processes, including formal handling of cross-company meetings, data requests, documentation, and CSI-sensitive workflows described in the Project Comet guidance.
What You'll Do
  • Lead the architecture and implementation of production-grade data science and machine learning solutions, from problem framing through deployment and adoption.
  • Build scalable data products, models, and decision-support tools using statistical methods, machine learning, optimization, and modern analytics engineering practices.
  • Partner with business leaders, engineering, IT, manufacturing, quality, finance, and other cross-functional teams to identify high-value opportunities and prioritize work with clear business impact.
  • Translate ambiguous business problems into structured analytical approaches, measurable success criteria, and deliverable roadmaps.
  • Design and maintain reliable data pipelines, feature pipelines, experimentation frameworks, and model monitoring practices.
  • Drive the responsible use of AI across the organization by developing reusable frameworks, templates, evaluation approaches, and best practices for enterprise adoption.
  • Serve as a technical mentor to data scientists, analysts, and engineers; raise the bar on coding, experimentation, documentation, and stakeholder communication.
  • Create executive-ready narratives, visualizations, and recommendations that connect technical findings to business outcomes.
  • Partner with data platform and governance teams to ensure solutions meet requirements for security, compliance, and maintainability.
  • Help shape standards for model lifecycle management, MLOps, analytics engineering, and AI solution delivery.
  • Contribute to integration planning and enterprise analytics initiatives while following approved protocols for meetings, shared materials, data requests, and CSI/non-CSI handling where applicable. Project Comet guidance requires legally approved agendas for certain new cross-company meetings, use of the Data Request List for shared data, and routing potentially sensitive data through the appropriate review path or clean room process.

What Success Looks Like
  • You deliver analytics and AI solutions that produce measurable operational or financial impact.
  • You help the team focus on high-return opportunities that leadership can easily justify and support.
  • You raise technical quality while also improving speed, reuse, and maintainability.
  • You make data science more accessible to the business through better tools, communication, and enablement.
  • You influence decisions well beyond your direct project work.
  • You help the organization use data and AI more effectively without compromising governance, security, or compliance.

Required Qualifications
  • Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or a related technical field.
  • 8+ years of experience in data science, machine learning, analytics engineering, or data platform development, including experience delivering business-facing solutions in production.
  • Strong programming skills in Python and SQL.
  • Deep experience with statistical analysis, machine learning, feature engineering, model evaluation, and experimental design.
  • Strong experience building data pipelines and working with modern data platforms and cloud analytics ecosystems.
  • Demonstrated ability to own ambiguous, high-impact problems and drive them through to adoption.
  • Experience partnering with senior stakeholders and influencing decisions across technical and non-technical groups.
  • Strong written and verbal communication skills, including the ability to explain complex concepts clearly to executives and business partners.
  • Proven ability to mentor others and lead technically without direct authority.

Preferred Qualifications
  • Advanced degree in a quantitative or technical field.
  • Experience in semiconductor, manufacturing, operations, supply chain, quality, or related industrial domains.
  • Experience building and operationalizing AI/ML solutions at enterprise scale.
  • Experience with MLOps, model monitoring, and deployment workflows.
  • Experience with Databricks, Spark, orchestration tools, BI platforms, and modern software engineering practices.
  • Familiarity with secure data environments and regulated data handling.
  • Experience working in environments that require balancing innovation with compliance, governance, and business urgency.
  • Exposure to enterprise AI enablement, internal tooling, or organization-wide adoption programs.

Technical Skills
  • Python, SQL
  • Machine learning, statistics, optimization, experimentation
  • Data modeling, ETL/ELT, analytics engineering
  • Cloud and distributed data platforms
  • BI and visualization tools
  • Git-based development workflows and production-quality software practices
  • MLOps and model lifecycle management
  • Data governance, documentation, and reproducibility

Leadership Expectations
  • Acts like an owner and focuses on business value, not just technical elegance.
  • Brings an abundance mindset and collaborates across organizational boundaries.
  • Balances strategic thinking with hands-on execution.
  • Pushes for clarity, rigor, and practical outcomes.
  • Elevates the team through mentorship, standards, and example.
  • Exercises strong judgment around sensitive data, stakeholder alignment, and enterprise constraints.

Sample Responsibilities by Problem Type
  • Build predictive and optimization models that improve yield, quality, throughput, cost, or planning.
  • Develop AI-enabled tools that scale analyst and engineer productivity.
  • Create reusable data products that standardize metrics, reduce manual effort, and improve decision speed.
  • Lead diagnostic and exploratory analyses on complex manufacturing, product, or enterprise datasets.
  • Establish frameworks for model governance, evaluation, and business adoption.

This position is not eligible for visa sponsorship by the Company.
#LI-SM1
MAKE A DIFFERENCE AT QORVO
We are Qorvo. We do more than create innovative RF and Power solutions for the mobile, defense and infrastructure markets - we are a place to innovate and shape the future of wireless communications. It starts with our employees. As a unified global team, we bring a commitment to excellence, growth and a passion for creating what's next. Explore the possibilities with us.
We are an Equal Employment Opportunity (EEO) employer and welcome all qualified applicants. Applicants will receive fair and impartial consideration without regard to any characteristics protected by applicable law, including race, color, religion, sex (as defined by law), national origin, age, military or veteran status, genetic information, or disability.
Qorvo is an E-Verify Employer. For more information, please see the Right to Work and E-Verify Participation posters.

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